Deep learning is an evolutionary advancement in the field of machine learning. The technique has been adopted in several areas where the computer after processing volumes of data are expected to make intelligent decisions. An important field of application for deep learning is the area of biometrics wherein the patterns within the uniquely human traits are recognized. Recently, many systems and applications applied deep learning for biometric systems. The deep network is trained on the vast range of patterns, and once the network has learnt all the unique features from the data set, it can be used to recognize similar patterns. Biometric technology that is being widely used by security applications includes recognition based on face, fingerprint, iris, ear, palm-print, voice and gait. This paper provides an overview of some systems and applications that applied deep learning for biometric systems and classifying them according to biometrics modalities. Moreover, we are reviewing the existing system and performance indicators. After a detailed analysis of several existing approaches that combine biometric system with deep learning methods, we draw our conclusion.