The majority of breast cancer metastasis spreads through the axillary lymph nodes. It is challenging to classify whether there is disease or no-disease axillary lymph nodes because they are small and cluster together. We implemented a convolutional-neural network for automatic classification of diseased versus non-diseased axillary lymph nodes by analyzing data from standard clinical breast MRI. Data were assigned randomly to 70/30 as training/validation set. The results showed the remarkable agreement with ground truths, with 86.7% accuracy. This approach may prove useful for automatically detecting lymph nodes metastasis on MRI in clinical settings in breast cancer patients.