The paper presents an overview of Facial Expression Recognition methods using deep learning models that have been reviewed from published papers in reputable journals and conferences. Based on these studies, the authors have categorized the methods into five groups, including Convolutional Neural Network, Generative Adversarial Networks, Recurrent Neural Network, Transfer Learning and Other Methods and Signal-based Methods. In each group, the authors summarize prominent methods and comparative results. From these groups of methods, the authors have suggested a general process for the Facial Expression Recognition problem consisting of six steps of Problem Statement, Image preparation, Data Pre-processing, Feature extraction, Deep learning approaches and Facial expression classification. The paper provides researchers in the field of Facial Expression Recognition or newcomers to this field with an overview as well as a basis for developing in-depth research or developing solutions and models applied to related areas.