Statistical classification has been popular among various fields and stayed in the limelight of scientists of those fields. Examples of the fields include clinical trials where the statistical classification of patients is indispensable to predict the clinical courses of diseases. Considering the negative impact of diseases on performing daily tasks, correctly classifying patients based on the clinical information is vital in that we need to identify patients of the high-risk group to develop a severe state and arrange medical treatment for them at an opportune moment. Deep learning - a part of artificial intelligence - has gained much attention, and research on it burgeons during past decades. It is a veritable technique which was originally designed for the classification, and hence, the EzDL package can provide sublime solutions to various challenging classification problems encountered in the clinical trials. The EzDL package is based on the back-propagation algorithm which performs a multi-layer feed-forward neural network. This package contains two functions: Buddle_Main() and Buddle_Predict(). Buddle_Main() builds a feed-forward neural network model and trains the model. Buddle_Predict() provokes the trained model which is the output of Buddle_Main(), classifies given data, and make a final prediction for the data.