diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index e3306b3..0e8d3c5 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -453,6 +453,7 @@
     m_ParserFunctions[tflite::BuiltinOperator_ADD]               =  &TfLiteParser::ParseAdd;
     m_ParserFunctions[tflite::BuiltinOperator_MUL]               =  &TfLiteParser::ParseMul;
     m_ParserFunctions[tflite::BuiltinOperator_MEAN]              =  &TfLiteParser::ParseMean;
+    m_ParserFunctions[tflite::BuiltinOperator_PAD]               =  &TfLiteParser::ParsePad;
 }
 
 void TfLiteParser::ResetParser()
@@ -1086,6 +1087,41 @@
     RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
 }
 
+void TfLiteParser::ParsePad(size_t subgraphIndex, size_t operatorIndex)
+{
+    CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+
+    TfLiteParser::TensorRawPtrVector inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+
+    TfLiteParser::TensorRawPtrVector outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(outputs.size(), 1);
+
+    armnn::TensorInfo padTensorInfo = ToTensorInfo(inputs[1]);
+    BufferRawPtr bufferPtr = GetBuffer(m_Model, inputs[1]->buffer);
+
+    std::vector<unsigned int> padBuffer(padTensorInfo.GetNumElements());
+    ::memcpy(padBuffer.data(), bufferPtr->data.data(), padTensorInfo.GetNumBytes());
+
+    size_t step = 2;
+    armnn::PadDescriptor desc;
+    for (unsigned int i = 0; i < padTensorInfo.GetNumElements() / step; ++i)
+    {
+        desc.m_PadList.emplace_back(padBuffer[i * step], padBuffer[i * step + 1]);
+    }
+
+    auto layerName = boost::str(boost::format("Pad:%1%:%2%") % subgraphIndex % operatorIndex);
+    IConnectableLayer* layer = m_Network->AddPadLayer(desc, layerName.c_str());
+
+    TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
+
+    auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
+}
+
 void TfLiteParser::ParseRelu(size_t subgraphIndex, size_t operatorIndex)
 {
     CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp
index 581e012..6c26437 100644
--- a/src/armnnTfLiteParser/TfLiteParser.hpp
+++ b/src/armnnTfLiteParser/TfLiteParser.hpp
@@ -104,6 +104,7 @@
     void ParseAdd(size_t subgraphIndex, size_t operatorIndex);
     void ParseMul(size_t subgraphIndex, size_t operatorIndex);
     void ParseMean(size_t subgraphIndex, size_t operatorIndex);
+    void ParsePad(size_t subgraphIndex, size_t operatorIndex);
 
     void ParsePool(size_t subgraphIndex, size_t operatorIndex, armnn::PoolingAlgorithm algorithm);
 
diff --git a/src/armnnTfLiteParser/test/Pad.cpp b/src/armnnTfLiteParser/test/Pad.cpp
new file mode 100644
index 0000000..09b744a
--- /dev/null
+++ b/src/armnnTfLiteParser/test/Pad.cpp
@@ -0,0 +1,104 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersFixture.hpp"
+#include "../TfLiteParser.hpp"
+
+#include <string>
+#include <iostream>
+
+BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)
+
+struct PadFixture : public ParserFlatbuffersFixture
+{
+    explicit PadFixture(const std::string & inputShape,
+                        const std::string & outputShape,
+                        const std::string & padListShape,
+                        const std::string & padListData)
+    {
+        m_JsonString = R"(
+            {
+                "version": 3,
+                "operator_codes": [ { "builtin_code": "PAD" } ],
+                "subgraphs": [ {
+                    "tensors": [
+                        {
+                            "shape": )" + inputShape + R"(,
+                            "type": "FLOAT32",
+                            "buffer": 0,
+                            "name": "inputTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        },
+                        {
+                             "shape": )" + outputShape + R"(,
+                             "type": "FLOAT32",
+                             "buffer": 1,
+                             "name": "outputTensor",
+                             "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        },
+                        {
+                             "shape": )" + padListShape + R"( ,
+                             "type": "INT32",
+                             "buffer": 2,
+                             "name": "padList",
+                             "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                             }
+                        }
+                    ],
+                    "inputs": [ 0 ],
+                    "outputs": [ 1 ],
+                    "operators": [
+                        {
+                            "opcode_index": 0,
+                            "inputs": [ 0, 2 ],
+                            "outputs": [ 1 ],
+                            "custom_options_format": "FLEXBUFFERS"
+                        }
+                    ],
+                } ],
+                "buffers" : [
+                    { },
+                    { },
+                    { "data": )" + padListData + R"(, },
+                ]
+            }
+        )";
+      SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+    }
+};
+
+struct SimplePadFixture : public PadFixture
+{
+    SimplePadFixture() : PadFixture("[ 2, 3 ]", "[ 4, 7 ]", "[ 2, 2 ]",
+                                    "[  1,0,0,0, 1,0,0,0, 2,0,0,0, 2,0,0,0 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParsePad, SimplePadFixture)
+{
+    RunTest<2, float>(0,
+                      {{ "inputTensor",  { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f }}},
+                      {{ "outputTensor", { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+                                           0.0f, 0.0f, 1.0f, 2.0f, 3.0f, 0.0f, 0.0f,
+                                           0.0f, 0.0f, 4.0f, 5.0f, 6.0f, 0.0f, 0.0f,
+                                           0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()
+