diff --git a/common/src/main/java/org/opensearch/ml/common/output/model/ModelTensorOutput.java b/common/src/main/java/org/opensearch/ml/common/output/model/ModelTensorOutput.java
index 32f3318718..ca485ec05b 100644
--- a/common/src/main/java/org/opensearch/ml/common/output/model/ModelTensorOutput.java
+++ b/common/src/main/java/org/opensearch/ml/common/output/model/ModelTensorOutput.java
@@ -5,6 +5,8 @@
 
 package org.opensearch.ml.common.output.model;
 
+import static org.opensearch.core.xcontent.XContentParserUtils.ensureExpectedToken;
+
 import java.io.IOException;
 import java.util.ArrayList;
 import java.util.List;
@@ -12,6 +14,7 @@
 import org.opensearch.core.common.io.stream.StreamInput;
 import org.opensearch.core.common.io.stream.StreamOutput;
 import org.opensearch.core.xcontent.XContentBuilder;
+import org.opensearch.core.xcontent.XContentParser;
 import org.opensearch.ml.common.annotation.MLAlgoOutput;
 import org.opensearch.ml.common.output.MLOutput;
 import org.opensearch.ml.common.output.MLOutputType;
@@ -79,4 +82,24 @@ protected MLOutputType getType() {
         return OUTPUT_TYPE;
     }
 
+    public static ModelTensorOutput parse(XContentParser parser) throws IOException {
+        List<ModelTensors> mlModelOutputs = new ArrayList<>();
+
+        ensureExpectedToken(XContentParser.Token.START_OBJECT, parser.currentToken(), parser);
+        while (parser.nextToken() != XContentParser.Token.END_OBJECT) {
+            String fieldName = parser.currentName();
+            parser.nextToken();
+
+            if (fieldName.equals(INFERENCE_RESULT_FIELD)) {
+                ensureExpectedToken(XContentParser.Token.START_ARRAY, parser.currentToken(), parser);
+                while (parser.nextToken() != XContentParser.Token.END_ARRAY) {
+                    mlModelOutputs.add(ModelTensors.parse(parser));
+                }
+            } else {
+                parser.skipChildren();
+            }
+        }
+
+        return ModelTensorOutput.builder().mlModelOutputs(mlModelOutputs).build();
+    }
 }
diff --git a/common/src/main/java/org/opensearch/ml/common/output/model/ModelTensors.java b/common/src/main/java/org/opensearch/ml/common/output/model/ModelTensors.java
index 5622057951..8177a6ed56 100644
--- a/common/src/main/java/org/opensearch/ml/common/output/model/ModelTensors.java
+++ b/common/src/main/java/org/opensearch/ml/common/output/model/ModelTensors.java
@@ -5,6 +5,8 @@
 
 package org.opensearch.ml.common.output.model;
 
+import static org.opensearch.core.xcontent.XContentParserUtils.ensureExpectedToken;
+
 import java.io.IOException;
 import java.nio.ByteBuffer;
 import java.util.ArrayList;
@@ -17,6 +19,7 @@
 import org.opensearch.core.common.io.stream.Writeable;
 import org.opensearch.core.xcontent.ToXContentObject;
 import org.opensearch.core.xcontent.XContentBuilder;
+import org.opensearch.core.xcontent.XContentParser;
 import org.opensearch.ml.common.exception.MLException;
 
 import lombok.Builder;
@@ -139,4 +142,33 @@ public static ModelTensors fromBytes(byte[] bytes) {
             throw new MLException(errorMsg, e);
         }
     }
+
+    public static ModelTensors parse(XContentParser parser) throws IOException {
+        Integer statusCode = null;
+        List<ModelTensor> mlModelTensors = new ArrayList<>();
+        ensureExpectedToken(XContentParser.Token.START_OBJECT, parser.currentToken(), parser);
+
+        while (parser.nextToken() != XContentParser.Token.END_OBJECT) {
+            String fieldName = parser.currentName();
+            parser.nextToken();
+
+            switch (fieldName) {
+                case STATUS_CODE_FIELD:
+                    statusCode = parser.intValue(false);
+                    break;
+                case OUTPUT_FIELD:
+                    ensureExpectedToken(XContentParser.Token.START_ARRAY, parser.currentToken(), parser);
+                    while (parser.nextToken() != XContentParser.Token.END_ARRAY) {
+                        mlModelTensors.add(ModelTensor.parser(parser));
+                    }
+                    break;
+                default:
+                    parser.skipChildren();
+                    break;
+            }
+        }
+        ModelTensors modelTensors = ModelTensors.builder().mlModelTensors(mlModelTensors).build();
+        modelTensors.setStatusCode(statusCode);
+        return modelTensors;
+    }
 }
diff --git a/common/src/test/java/org/opensearch/ml/common/output/model/ModelTensorOutputTest.java b/common/src/test/java/org/opensearch/ml/common/output/model/ModelTensorOutputTest.java
index 67690ed2bf..b4a79afb98 100644
--- a/common/src/test/java/org/opensearch/ml/common/output/model/ModelTensorOutputTest.java
+++ b/common/src/test/java/org/opensearch/ml/common/output/model/ModelTensorOutputTest.java
@@ -14,7 +14,13 @@
 import org.junit.Before;
 import org.junit.Test;
 import org.opensearch.common.io.stream.BytesStreamOutput;
+import org.opensearch.common.xcontent.LoggingDeprecationHandler;
+import org.opensearch.common.xcontent.XContentType;
 import org.opensearch.core.common.io.stream.StreamInput;
+import org.opensearch.core.xcontent.NamedXContentRegistry;
+import org.opensearch.core.xcontent.XContentBuilder;
+import org.opensearch.core.xcontent.XContentParser;
+import org.opensearch.ml.common.TestHelper;
 import org.opensearch.ml.common.output.MLOutputType;
 
 public class ModelTensorOutputTest {
@@ -61,6 +67,109 @@ public void readInputStream_NullField() throws IOException {
         });
     }
 
+    @Test
+    public void parse_Success() throws IOException {
+        XContentBuilder builder = XContentBuilder.builder(XContentType.JSON.xContent());
+        builder.startObject();
+        builder.startArray(ModelTensorOutput.INFERENCE_RESULT_FIELD);
+
+        builder.startObject();
+        builder.startArray("output");
+
+        builder.startObject();
+        builder.field("name", "test");
+        builder.field("data_type", "FLOAT32");
+        builder.field("shape", new long[] { 1, 3 });
+        builder.field("data", value);
+        builder.endObject();
+
+        builder.endArray();
+        builder.endObject();
+
+        builder.endArray();
+        builder.endObject();
+
+        String jsonStr = TestHelper.xContentBuilderToString(builder);
+
+        XContentParser parser = XContentType.JSON
+            .xContent()
+            .createParser(NamedXContentRegistry.EMPTY, LoggingDeprecationHandler.INSTANCE, jsonStr);
+        parser.nextToken();
+
+        ModelTensorOutput parsedOutput = ModelTensorOutput.parse(parser);
+
+        assertEquals(1, parsedOutput.getMlModelOutputs().size());
+        ModelTensors modelTensors = parsedOutput.getMlModelOutputs().get(0);
+        assertEquals(1, modelTensors.getMlModelTensors().size());
+        ModelTensor modelTensor = modelTensors.getMlModelTensors().get(0);
+        assertEquals("test", modelTensor.getName());
+        assertEquals(value.length, modelTensor.getData().length);
+        assertEquals(value[0].doubleValue(), modelTensor.getData()[0].doubleValue(), 0.0001);
+        assertArrayEquals(new long[] { 1, 3 }, modelTensor.getShape());
+        assertEquals(MLResultDataType.FLOAT32, modelTensor.getDataType());
+    }
+
+    @Test
+    public void parse_EmptyObject() throws IOException {
+        XContentBuilder builder = XContentBuilder.builder(XContentType.JSON.xContent());
+        builder.startObject();
+        builder.endObject();
+
+        String jsonStr = TestHelper.xContentBuilderToString(builder);
+
+        XContentParser parser = XContentType.JSON
+            .xContent()
+            .createParser(NamedXContentRegistry.EMPTY, LoggingDeprecationHandler.INSTANCE, jsonStr);
+        parser.nextToken();
+
+        ModelTensorOutput parsedOutput = ModelTensorOutput.parse(parser);
+
+        assertEquals(0, parsedOutput.getMlModelOutputs().size());
+    }
+
+    @Test
+    public void parse_SkipIrrelevantFields() throws IOException {
+        XContentBuilder builder = XContentBuilder.builder(XContentType.JSON.xContent());
+        builder.startObject();
+
+        builder.field("irrelevant_field", "irrelevant_value");
+
+        builder.startArray(ModelTensorOutput.INFERENCE_RESULT_FIELD);
+        builder.startObject();
+        builder.startArray("output");
+        builder.startObject();
+        builder.field("name", "test");
+        builder.field("data_type", "FLOAT32");
+        builder.field("shape", new long[] { 1, 3 });
+        builder.field("data", value);
+        builder.endObject();
+        builder.endArray();
+        builder.endObject();
+        builder.endArray();
+
+        builder.field("another_irrelevant_field", "another_value");
+
+        builder.endObject();
+
+        String jsonStr = TestHelper.xContentBuilderToString(builder);
+
+        XContentParser parser = XContentType.JSON
+            .xContent()
+            .createParser(NamedXContentRegistry.EMPTY, LoggingDeprecationHandler.INSTANCE, jsonStr);
+        parser.nextToken();
+
+        ModelTensorOutput parsedOutput = ModelTensorOutput.parse(parser);
+
+        assertEquals(1, parsedOutput.getMlModelOutputs().size());
+        ModelTensors modelTensors = parsedOutput.getMlModelOutputs().get(0);
+        assertEquals(1, modelTensors.getMlModelTensors().size());
+        ModelTensor modelTensor = modelTensors.getMlModelTensors().get(0);
+        assertEquals("test", modelTensor.getName());
+        assertEquals(value.length, modelTensor.getData().length);
+        assertEquals(value[0].doubleValue(), modelTensor.getData()[0].doubleValue(), 0.0001);
+        assertArrayEquals(new long[] { 1, 3 }, modelTensor.getShape());
+    }
+
     private void readInputStream(ModelTensorOutput input, Consumer<ModelTensorOutput> verify) throws IOException {
         BytesStreamOutput bytesStreamOutput = new BytesStreamOutput();
         input.writeTo(bytesStreamOutput);
diff --git a/common/src/test/java/org/opensearch/ml/common/output/model/ModelTensorsTest.java b/common/src/test/java/org/opensearch/ml/common/output/model/ModelTensorsTest.java
index a4f7dc51b1..f3f7f98b6c 100644
--- a/common/src/test/java/org/opensearch/ml/common/output/model/ModelTensorsTest.java
+++ b/common/src/test/java/org/opensearch/ml/common/output/model/ModelTensorsTest.java
@@ -6,6 +6,8 @@
 package org.opensearch.ml.common.output.model;
 
 import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertNotNull;
+import static org.junit.Assert.assertNull;
 import static org.opensearch.core.xcontent.ToXContent.EMPTY_PARAMS;
 
 import java.io.IOException;
@@ -17,9 +19,12 @@
 import org.junit.Test;
 import org.junit.rules.ExpectedException;
 import org.opensearch.common.io.stream.BytesStreamOutput;
+import org.opensearch.common.xcontent.LoggingDeprecationHandler;
 import org.opensearch.common.xcontent.XContentType;
 import org.opensearch.core.common.io.stream.StreamInput;
+import org.opensearch.core.xcontent.NamedXContentRegistry;
 import org.opensearch.core.xcontent.XContentBuilder;
+import org.opensearch.core.xcontent.XContentParser;
 import org.opensearch.ml.common.TestHelper;
 
 public class ModelTensorsTest {
@@ -28,6 +33,7 @@ public class ModelTensorsTest {
     public ExpectedException exceptionRule = ExpectedException.none();
     private ModelTensors modelTensors;
     private ModelResultFilter modelResultFilter;
+    private Number[] testData;
 
     @Before
     public void setUp() {
@@ -40,10 +46,11 @@ public void setUp() {
             .targetResponsePositions(Arrays.asList(position))
             .build();
 
+        testData = new Number[] { 1, 2, 3 };
         ModelTensor modelTensor = ModelTensor
             .builder()
             .name("model_tensor")
-            .data(new Number[] { 1, 2, 3 })
+            .data(testData)
             .shape(new long[] { 1, 2, 3, })
             .dataType(MLResultDataType.INT32)
             .byteBuffer(ByteBuffer.wrap(new byte[] { 0, 1, 0, 1 }))
@@ -120,4 +127,151 @@ public void test_ToAndFromBytes() throws IOException {
         ModelTensors tensors = ModelTensors.fromBytes(bytes);
         // assertEquals(modelTensors.getMlModelTensors(), tensors.getMlModelTensors());
     }
+
+    @Test
+    public void parse_Success_WithOutput() throws IOException {
+        XContentBuilder builder = XContentBuilder.builder(XContentType.JSON.xContent());
+        builder.startObject();
+        builder.startArray(ModelTensors.OUTPUT_FIELD);
+
+        builder.startObject();
+        builder.field("name", "test_tensor");
+        builder.field("data_type", "FLOAT32");
+        builder.field("shape", new long[] { 1, 3 });
+        builder.field("data", new Float[] { 1.0f, 2.0f, 3.0f });
+        builder.endObject();
+
+        builder.endArray();
+        builder.endObject();
+
+        String jsonStr = TestHelper.xContentBuilderToString(builder);
+
+        XContentParser parser = XContentType.JSON
+            .xContent()
+            .createParser(NamedXContentRegistry.EMPTY, LoggingDeprecationHandler.INSTANCE, jsonStr);
+        parser.nextToken();
+
+        ModelTensors parsedTensors = ModelTensors.parse(parser);
+
+        assertNotNull(parsedTensors.getMlModelTensors());
+        assertEquals(1, parsedTensors.getMlModelTensors().size());
+        ModelTensor modelTensor = parsedTensors.getMlModelTensors().get(0);
+        assertEquals("test_tensor", modelTensor.getName());
+        assertEquals(3, modelTensor.getData().length);
+        // Compare the first value using double conversion to handle type differences
+        assertEquals(1.0, modelTensor.getData()[0].doubleValue(), 0.0001);
+        assertNull(parsedTensors.getStatusCode());
+    }
+
+    @Test
+    public void parse_Success_WithStatusCode() throws IOException {
+        XContentBuilder builder = XContentBuilder.builder(XContentType.JSON.xContent());
+        builder.startObject();
+        builder.field(ModelTensors.STATUS_CODE_FIELD, 200);
+        builder.endObject();
+
+        String jsonStr = TestHelper.xContentBuilderToString(builder);
+
+        XContentParser parser = XContentType.JSON
+            .xContent()
+            .createParser(NamedXContentRegistry.EMPTY, LoggingDeprecationHandler.INSTANCE, jsonStr);
+        parser.nextToken();
+
+        ModelTensors parsedTensors = ModelTensors.parse(parser);
+
+        assertEquals(Integer.valueOf(200), parsedTensors.getStatusCode());
+        assertNotNull(parsedTensors.getMlModelTensors());
+        assertEquals(0, parsedTensors.getMlModelTensors().size());
+    }
+
+    @Test
+    public void parse_Success_WithOutputAndStatusCode() throws IOException {
+        XContentBuilder builder = XContentBuilder.builder(XContentType.JSON.xContent());
+        builder.startObject();
+
+        builder.field(ModelTensors.STATUS_CODE_FIELD, 200);
+
+        builder.startArray(ModelTensors.OUTPUT_FIELD);
+        builder.startObject();
+        builder.field("name", "test_tensor");
+        builder.field("data_type", "INT32");
+        builder.field("shape", new long[] { 1, 2 });
+        builder.field("data", new Integer[] { 1, 2 });
+        builder.endObject();
+        builder.endArray();
+
+        builder.endObject();
+
+        String jsonStr = TestHelper.xContentBuilderToString(builder);
+
+        XContentParser parser = XContentType.JSON
+            .xContent()
+            .createParser(NamedXContentRegistry.EMPTY, LoggingDeprecationHandler.INSTANCE, jsonStr);
+        parser.nextToken();
+
+        ModelTensors parsedTensors = ModelTensors.parse(parser);
+
+        assertEquals(Integer.valueOf(200), parsedTensors.getStatusCode());
+        assertNotNull(parsedTensors.getMlModelTensors());
+        assertEquals(1, parsedTensors.getMlModelTensors().size());
+        ModelTensor modelTensor = parsedTensors.getMlModelTensors().get(0);
+        assertEquals("test_tensor", modelTensor.getName());
+    }
+
+    @Test
+    public void parse_EmptyObject() throws IOException {
+        XContentBuilder builder = XContentBuilder.builder(XContentType.JSON.xContent());
+        builder.startObject();
+        builder.endObject();
+
+        String jsonStr = TestHelper.xContentBuilderToString(builder);
+
+        XContentParser parser = XContentType.JSON
+            .xContent()
+            .createParser(NamedXContentRegistry.EMPTY, LoggingDeprecationHandler.INSTANCE, jsonStr);
+        parser.nextToken();
+
+        ModelTensors parsedTensors = ModelTensors.parse(parser);
+
+        assertNotNull(parsedTensors.getMlModelTensors());
+        assertEquals(0, parsedTensors.getMlModelTensors().size());
+        assertNull(parsedTensors.getStatusCode());
+    }
+
+    @Test
+    public void parse_SkipIrrelevantFields() throws IOException {
+        XContentBuilder builder = XContentBuilder.builder(XContentType.JSON.xContent());
+        builder.startObject();
+
+        builder.field("irrelevant_field", "irrelevant_value");
+
+        builder.startArray(ModelTensors.OUTPUT_FIELD);
+        builder.startObject();
+        builder.field("name", "test_tensor");
+        builder.field("data_type", "INT32");
+        builder.field("shape", new long[] { 1, 2 });
+        builder.field("data", new Integer[] { 1, 2 });
+        builder.endObject();
+        builder.endArray();
+
+        builder.field(ModelTensors.STATUS_CODE_FIELD, 404);
+
+        builder.field("another_irrelevant_field", "another_value");
+
+        builder.endObject();
+
+        String jsonStr = TestHelper.xContentBuilderToString(builder);
+
+        XContentParser parser = XContentType.JSON
+            .xContent()
+            .createParser(NamedXContentRegistry.EMPTY, LoggingDeprecationHandler.INSTANCE, jsonStr);
+        parser.nextToken();
+        ModelTensors parsedTensors = ModelTensors.parse(parser);
+
+        assertEquals(Integer.valueOf(404), parsedTensors.getStatusCode());
+        assertNotNull(parsedTensors.getMlModelTensors());
+        assertEquals(1, parsedTensors.getMlModelTensors().size());
+        ModelTensor modelTensor = parsedTensors.getMlModelTensors().get(0);
+        assertEquals("test_tensor", modelTensor.getName());
+    }
 }