This chapter presents the problem of identifying people through gait, a promising biometric method with significant benefits over traditional methods. However, challenges such as variations in gait due to different factors and the complexities of the environment still need to be overcome. Objectives are also presented, such as conducting a systematic review of deep learning models for gait-based identification, analyzing and comparing existing methods, and investigating current challenges. Finally the end, the book’s structure is presented, ranging from fundamental concepts to method comparisons and conclusions.