diff --git a/src/backends/backendsCommon/test/layerTests/MeanTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/MeanTestImpl.hpp
new file mode 100644
index 0000000..d0bdfa4
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/MeanTestImpl.hpp
@@ -0,0 +1,178 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "LayerTestResult.hpp"
+
+#include <ResolveType.hpp>
+
+#include <backendsCommon/IBackendInternal.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+namespace
+{
+
+template<armnn::DataType ArmnnType, typename T, std::size_t InputDim, std::size_t OutputDim>
+LayerTestResult<T, OutputDim> MeanTestHelper(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        const unsigned int* inputShape,
+        const std::vector<float>& inputData,
+        const std::vector<unsigned int>& axis,
+        bool keepDims,
+        const unsigned int* outputShape,
+        const std::vector<float>& outputData,
+        float scale = 1.0f,
+        int32_t offset = 0)
+{
+    armnn::TensorInfo inputTensorInfo(InputDim, inputShape, ArmnnType);
+    armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, ArmnnType);
+
+    inputTensorInfo.SetQuantizationScale(scale);
+    inputTensorInfo.SetQuantizationOffset(offset);
+
+    outputTensorInfo.SetQuantizationScale(scale);
+    outputTensorInfo.SetQuantizationOffset(offset);
+
+    auto input = MakeTensor<T, InputDim>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputData, inputTensorInfo));
+
+    LayerTestResult<T, OutputDim> result(outputTensorInfo);
+    result.outputExpected = MakeTensor<T, OutputDim>(
+            outputTensorInfo, ConvertToDataType<ArmnnType>(outputData, outputTensorInfo));
+
+    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+    armnn::MeanQueueDescriptor data;
+    data.m_Parameters.m_Axis = axis;
+    data.m_Parameters.m_KeepDims = keepDims;
+    armnn::WorkloadInfo info;
+    AddInputToWorkload(data,  info, inputTensorInfo, inputHandle.get());
+    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+
+    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMean(data, info);
+
+    inputHandle->Allocate();
+    outputHandle->Allocate();
+
+    CopyDataToITensorHandle(inputHandle.get(), input.origin());
+
+    workload->PostAllocationConfigure();
+    workload->Execute();
+
+    CopyDataFromITensorHandle(result.output.origin(), outputHandle.get());
+
+    return result;
+}
+
+} // anonymous namespace
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 1> MeanSimpleTest(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = { 3, 2 };
+    const unsigned int outputShape[] = { 1 };
+
+    std::vector<float> input({ 1.5f, 1.5f, 2.5f, 2.5f, 3.5f, 3.5f });
+    std::vector<float> output({ 2.5f });
+
+    return MeanTestHelper<ArmnnType, T, 2, 1>(
+            workloadFactory, memoryManager, inputShape, input, {}, false, outputShape, output);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 3> MeanSimpleAxisTest(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = { 2, 3, 1, 2 };
+    const unsigned int outputShape[] = { 3, 1, 2 };
+
+    std::vector<float> input({ 1.5f, 2.5f, 3.5f, 4.5f, 5.5f, 6.5f, 1.5f, 2.5f, 3.5f, 4.5f, 5.5f, 6.5f });
+    std::vector<float> output({ 1.5f, 2.5f, 3.5f, 4.5f, 5.5f, 6.5f });
+
+    return MeanTestHelper<ArmnnType, T, 4, 3>(
+            workloadFactory, memoryManager, inputShape, input, { 0 }, false, outputShape, output);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> MeanKeepDimsTest(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = { 1, 1, 3, 2 };
+    const unsigned int outputShape[] = { 1, 1, 1, 2 };
+
+    std::vector<float> input({ 1.5f, 1.5f, 2.5f, 2.5f, 3.5f, 3.5f });
+    std::vector<float> output({ 2.5f, 2.5f });
+
+    return MeanTestHelper<ArmnnType, T, 4, 4>(
+            workloadFactory, memoryManager, inputShape, input, { 2 }, true, outputShape, output);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> MeanMultipleDimsTest(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = { 2, 3, 1, 2 };
+    const unsigned int outputShape[] = { 1, 3, 1, 1 };
+
+    std::vector<float> input({ 1.5f, 2.5f, 3.5f, 4.5f, 5.5f, 6.5f, 1.5f, 2.5f, 3.5f, 4.5f, 5.5f, 6.5 });
+    std::vector<float> output({ 2.0f, 4.0f, 6.0f });
+
+    return MeanTestHelper<ArmnnType, T, 4, 4>(
+            workloadFactory, memoryManager, inputShape, input, { 0, 3 }, true, outputShape, output);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 1> MeanVts1Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = { 4, 3, 2 };
+    const unsigned int outputShape[] = { 2 };
+
+    std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f,
+                               15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f });
+    std::vector<float> output({ 12.0f, 13.0f });
+
+    return MeanTestHelper<ArmnnType, T, 3, 1>(
+            workloadFactory, memoryManager, inputShape, input, { 0, 1 }, false, outputShape, output);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 3> MeanVts2Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = { 4, 3, 2 };
+    const unsigned int outputShape[] = { 1, 3, 1 };
+
+    std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f,
+                               15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f });
+    std::vector<float> output({ 10.5f, 12.5f, 14.5f });
+
+    return MeanTestHelper<ArmnnType, T, 3, 3>(
+            workloadFactory, memoryManager, inputShape, input, { 0, 2 }, true, outputShape, output);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 3> MeanVts3Test(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+    const unsigned int inputShape[] = { 1, 2, 2, 1 };
+    const unsigned int outputShape[] = { 1, 2, 1 };
+
+    std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f });
+    std::vector<float> output({ 1.5f, 3.5f });
+
+    return MeanTestHelper<ArmnnType, T, 4, 3>(
+            workloadFactory, memoryManager, inputShape, input, { 2 }, false, outputShape, output);
+}