diff --git a/src/armnnDeserializeParser/DeserializeParser.cpp b/src/armnnDeserializeParser/DeserializeParser.cpp
index 5ba92d5..0368cca 100644
--- a/src/armnnDeserializeParser/DeserializeParser.cpp
+++ b/src/armnnDeserializeParser/DeserializeParser.cpp
@@ -132,7 +132,8 @@
 m_ParserFunctions(Layer_MAX+1, &DeserializeParser::ParseUnsupportedLayer)
 {
     // register supported layers
-    m_ParserFunctions[Layer_AdditionLayer]   =  &DeserializeParser::ParseAdd;
+    m_ParserFunctions[Layer_AdditionLayer]         =  &DeserializeParser::ParseAdd;
+    m_ParserFunctions[Layer_MultiplicationLayer]   =  &DeserializeParser::ParseMultiplication;
 }
 
 DeserializeParser::LayerBaseRawPtr DeserializeParser::GetBaseLayer(const GraphPtr& graphPtr, unsigned int layerIndex)
@@ -145,6 +146,8 @@
             return graphPtr->layers()->Get(layerIndex)->layer_as_AdditionLayer()->base();
         case Layer::Layer_InputLayer:
            return graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->base();
+        case Layer::Layer_MultiplicationLayer:
+            return graphPtr->layers()->Get(layerIndex)->layer_as_MultiplicationLayer()->base();
         case Layer::Layer_OutputLayer:
             return graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->base();
         case Layer::Layer_NONE:
@@ -582,6 +585,26 @@
     RegisterOutputSlots(layerIndex, layer);
 }
 
+void DeserializeParser::ParseMultiplication(unsigned int layerIndex)
+{
+    CHECK_LAYERS(m_Graph, 0, layerIndex);
+    auto inputs = GetInputs(m_Graph, layerIndex);
+    CHECK_LOCATION();
+    CHECK_VALID_SIZE(inputs.size(), 2);
+
+    auto outputs = GetOutputs(m_Graph, layerIndex);
+    CHECK_VALID_SIZE(outputs.size(), 1);
+
+    auto layerName = boost::str(boost::format("Multiplication:%1%") % layerIndex);
+    IConnectableLayer* layer = m_Network->AddMultiplicationLayer(layerName.c_str());
+
+    armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    RegisterInputSlots(layerIndex, layer);
+    RegisterOutputSlots(layerIndex, layer);
+}
+
 }
 
 
diff --git a/src/armnnDeserializeParser/DeserializeParser.hpp b/src/armnnDeserializeParser/DeserializeParser.hpp
index 322826c..9edd959 100644
--- a/src/armnnDeserializeParser/DeserializeParser.hpp
+++ b/src/armnnDeserializeParser/DeserializeParser.hpp
@@ -64,6 +64,7 @@
 
     void ParseUnsupportedLayer(unsigned int serializeGraphIndex);
     void ParseAdd(unsigned int serializeGraphIndex);
+    void ParseMultiplication(unsigned int serializeGraphIndex);
 
     void RegisterOutputSlotOfConnection(uint32_t connectionIndex, armnn::IOutputSlot* slot);
     void RegisterInputSlotOfConnection(uint32_t connectionIndex, armnn::IInputSlot* slot);
diff --git a/src/armnnDeserializeParser/DeserializerSupport.md b/src/armnnDeserializeParser/DeserializerSupport.md
index 7135003..8e14334 100644
--- a/src/armnnDeserializeParser/DeserializerSupport.md
+++ b/src/armnnDeserializeParser/DeserializerSupport.md
@@ -7,5 +7,6 @@
 The Arm NN SDK Deserialize parser currently supports the following layers:
 
 * Addition
+* Multiplication
 
 More machine learning layers will be supported in future releases.
diff --git a/src/armnnDeserializeParser/test/DeserializeMultiplication.cpp b/src/armnnDeserializeParser/test/DeserializeMultiplication.cpp
new file mode 100644
index 0000000..f8eff16
--- /dev/null
+++ b/src/armnnDeserializeParser/test/DeserializeMultiplication.cpp
@@ -0,0 +1,161 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersSerializeFixture.hpp"
+#include "../DeserializeParser.hpp"
+
+#include <string>
+#include <iostream>
+
+BOOST_AUTO_TEST_SUITE(DeserializeParser)
+
+struct MultiplicationFixture : public ParserFlatbuffersSerializeFixture
+{
+    explicit MultiplicationFixture(const std::string & inputShape1,
+                                   const std::string & inputShape2,
+                                   const std::string & outputShape,
+                                   const std::string & dataType,
+                                   const std::string & activation="NONE")
+    {
+        m_JsonString = R"(
+        {
+                inputIds: [0, 1],
+                outputIds: [3],
+                layers: [
+                {
+                    layer_type: "InputLayer",
+                    layer: {
+                          base: {
+                                layerBindingId: 0,
+                                base: {
+                                    index: 0,
+                                    layerName: "InputLayer1",
+                                    layerType: "Input",
+                                    inputSlots: [{
+                                        index: 0,
+                                        connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                                    }],
+                                    outputSlots: [ {
+                                        index: 0,
+                                        tensorInfo: {
+                                            dimensions: )" + inputShape1 + R"(,
+                                            dataType: )" + dataType + R"(
+                                        },
+                                    }],
+                                 },}},
+                },
+                {
+                layer_type: "InputLayer",
+                layer: {
+                       base: {
+                            layerBindingId: 1,
+                            base: {
+                                  index:1,
+                                  layerName: "InputLayer2",
+                                  layerType: "Input",
+                                  inputSlots: [{
+                                      index: 0,
+                                      connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                                  }],
+                                  outputSlots: [ {
+                                      index: 0,
+                                      tensorInfo: {
+                                          dimensions: )" + inputShape2 + R"(,
+                                          dataType: )" + dataType + R"(
+                                      },
+                                  }],
+                                },}},
+                },
+                {
+                layer_type: "MultiplicationLayer",
+                layer : {
+                        base: {
+                             index:2,
+                             layerName: "MultiplicationLayer",
+                             layerType: "Multiplication",
+                             inputSlots: [
+                                            {
+                                             index: 0,
+                                             connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                                            },
+                                            {
+                                             index: 1,
+                                             connection: {sourceLayerIndex:1, outputSlotIndex:0 },
+                                            }
+                             ],
+                             outputSlots: [ {
+                                 index: 0,
+                                 tensorInfo: {
+                                     dimensions: )" + outputShape + R"(,
+                                     dataType: )" + dataType + R"(
+                                 },
+                             }],
+                            }},
+                },
+                {
+                layer_type: "OutputLayer",
+                layer: {
+                        base:{
+                              layerBindingId: 3,
+                              base: {
+                                    index: 3,
+                                    layerName: "OutputLayer",
+                                    layerType: "Output",
+                                    inputSlots: [{
+                                        index: 0,
+                                        connection: {sourceLayerIndex:2, outputSlotIndex:0 },
+                                    }],
+                                    outputSlots: [ {
+                                        index: 0,
+                                        tensorInfo: {
+                                            dimensions: )" + outputShape + R"(,
+                                            dataType: )" + dataType + R"(
+                                        },
+                                }],
+                            }}},
+                }]
+         }
+        )";
+        Setup();
+    }
+};
+
+
+struct SimpleMultiplicationFixture : MultiplicationFixture
+{
+    SimpleMultiplicationFixture() : MultiplicationFixture("[ 2, 2 ]",
+                                                          "[ 2, 2 ]",
+                                                          "[ 2, 2 ]",
+                                                          "QuantisedAsymm8") {}
+};
+
+struct SimpleMultiplicationFixture2 : MultiplicationFixture
+{
+    SimpleMultiplicationFixture2() : MultiplicationFixture("[ 2, 2, 1, 1 ]",
+                                                           "[ 2, 2, 1, 1 ]",
+                                                           "[ 2, 2, 1, 1 ]",
+                                                           "Float32") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(MultiplicationQuantisedAsymm8, SimpleMultiplicationFixture)
+{
+  RunTest<2, armnn::DataType::QuantisedAsymm8>(
+      0,
+      {{"InputLayer1", { 0, 1, 2, 3 }},
+      {"InputLayer2", { 4, 5, 6, 7 }}},
+      {{"OutputLayer", { 0, 5, 12, 21 }}});
+}
+
+BOOST_FIXTURE_TEST_CASE(MultiplicationFloat32, SimpleMultiplicationFixture2)
+{
+    RunTest<4, armnn::DataType::Float32>(
+    0,
+    {{"InputLayer1", { 100, 40, 226, 9 }},
+    {"InputLayer2", {   5,   8,  1, 12 }}},
+    {{"OutputLayer", { 500, 320, 226, 108 }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()