diff --git a/README.rst b/README.rst
index f66c1533ff..bacf953a20 100644
--- a/README.rst
+++ b/README.rst
@@ -173,9 +173,9 @@ MXNet SageMaker Estimators
 
 By using MXNet SageMaker Estimators, you can train and host MXNet models on Amazon SageMaker.
 
-Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``.
+Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.
 
-Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``.
+Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.
 
 We recommend that you use the latest supported version, because that's where we focus most of our development efforts.
 
diff --git a/doc/using_mxnet.rst b/doc/using_mxnet.rst
index c4fb3c5ec0..a951b5ce43 100644
--- a/doc/using_mxnet.rst
+++ b/doc/using_mxnet.rst
@@ -6,9 +6,9 @@ Using MXNet with the SageMaker Python SDK
 
 With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.
 
-Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
+Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.
 
-Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
+Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.
 
 Training with MXNet
 -------------------
@@ -806,23 +806,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f
 
 The Docker images have the following dependencies installed:
 
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| Dependencies            | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| Python                  |   2.7 or 3.5 |   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.6|
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| CUDA (GPU image only)   |          9.0 |         9.0 |         9.0 |         9.0 |         9.0 |         9.2 |
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| numpy                   |       1.13.3 |      1.13.3 |      1.13.3 |      1.14.5 |      1.14.6 |      1.16.3 |
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| onnx                    |          N/A |         N/A |         N/A |       1.2.1 |       1.2.1 |       1.4.1 |
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| keras-mxnet             |          N/A |         N/A |         N/A |         N/A |       2.2.2 |     2.2.4.1 |
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| Dependencies            | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| Python                  |   2.7 or 3.5 |   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.6|   2.7 or 3.6|
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| CUDA (GPU image only)   |          9.0 |         9.0 |         9.0 |         9.0 |         9.0 |         9.2 |        10.0 |
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| numpy                   |       1.13.3 |      1.13.3 |      1.13.3 |      1.14.5 |      1.14.6 |      1.16.3 |      1.14.5 |
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| onnx                    |          N/A |         N/A |         N/A |       1.2.1 |       1.2.1 |       1.4.1 |       1.4.1 |
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| keras-mxnet             |          N/A |         N/A |         N/A |         N/A |       2.2.2 |     2.2.4.1 |     2.2.4.1 |
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
 
 The Docker images extend Ubuntu 16.04.
 
-You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
+You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
 Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.
 
 You can visit the SageMaker MXNet container repositories here:
diff --git a/src/sagemaker/mxnet/README.rst b/src/sagemaker/mxnet/README.rst
index f0965cd38a..6582257d08 100644
--- a/src/sagemaker/mxnet/README.rst
+++ b/src/sagemaker/mxnet/README.rst
@@ -4,9 +4,9 @@ Using MXNet with the SageMaker Python SDK
 
 With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.
 
-Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
+Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.
 
-Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
+Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.
 
 For information about using MXNet with the SageMaker Python SDK, see https://sagemaker.readthedocs.io/en/stable/using_mxnet.html.
 
@@ -21,23 +21,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f
 
 The Docker images have the following dependencies installed:
 
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| Dependencies            | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| Python                  |   2.7 or 3.5 |   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.6|
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| CUDA (GPU image only)   |          9.0 |         9.0 |         9.0 |         9.0 |         9.0 |         9.2 |
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| numpy                   |       1.13.3 |      1.13.3 |      1.13.3 |      1.14.5 |      1.14.6 |      1.16.3 |
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| onnx                    |          N/A |         N/A |         N/A |       1.2.1 |       1.2.1 |       1.4.1 |
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
-| keras-mxnet             |          N/A |         N/A |         N/A |         N/A |       2.2.2 |     2.2.4.1 |
-+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| Dependencies            | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| Python                  |   2.7 or 3.5 |   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.5|   2.7 or 3.6|   2.7 or 3.6|
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| CUDA (GPU image only)   |          9.0 |         9.0 |         9.0 |         9.0 |         9.0 |         9.2 |        10.0 |
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| numpy                   |       1.13.3 |      1.13.3 |      1.13.3 |      1.14.5 |      1.14.6 |      1.16.3 |      1.14.5 |
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| onnx                    |          N/A |         N/A |         N/A |       1.2.1 |       1.2.1 |       1.4.1 |       1.4.1 |
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
+| keras-mxnet             |          N/A |         N/A |         N/A |         N/A |       2.2.2 |     2.2.4.1 |     2.2.4.1 |
++-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
 
 The Docker images extend Ubuntu 16.04.
 
-You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
+You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
 Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.
 
 You can visit the SageMaker MXNet container repositories here:
diff --git a/src/sagemaker/mxnet/estimator.py b/src/sagemaker/mxnet/estimator.py
index 81a81a768b..6cb552ff4b 100644
--- a/src/sagemaker/mxnet/estimator.py
+++ b/src/sagemaker/mxnet/estimator.py
@@ -34,7 +34,7 @@ class MXNet(Framework):
     __framework_name__ = "mxnet"
     _LOWEST_SCRIPT_MODE_VERSION = ["1", "3"]
 
-    LATEST_VERSION = "1.4"
+    LATEST_VERSION = "1.4.1"
     """The latest version of MXNet included in the SageMaker pre-built Docker images."""
 
     def __init__(
diff --git a/tests/conftest.py b/tests/conftest.py
index 00033e6fd2..588aaf9b97 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -135,6 +135,7 @@ def chainer_version(request):
         "1.3.0",
         "1.4",
         "1.4.0",
+        "1.4.1",
     ],
 )
 def mxnet_version(request):