The deep learning of kinetic models with the Weighted Ensemble Simulation Toolkit (Deep-WEST) method aims to provide well-sampled initial distribution to WE simulations. It is achieved by running a relatively short MD simulation and processing the trajectory data through the VAMP approach by employing neural networks. Initial conformations for WE simulations and their probabilistic values are extracted from the resultant MSMs. WE simulations are then run with this distribution, generating a more refined free energy landscape closer to the steady-state distribution. We have developed a DeepWEST package that au-tomates the entire process of running MD simulations for trajectory analysis, deep learning of kinetic models for generating MSMs through VAMPNets, and well-sampled initial conformations for running WE simulations. The entire workflow can be described below: