In present academic system, regular class attendance of students' plays a significant role in performance assessment and quality monitoring. The conventional methods practiced in most of the institutions are by calling names or signing on papers, which is highly time- consuming and insecure. This project presents the automatic attendance management system for convenience or data reliability. We are living in a world where everything is automated and linked online. The internet of things, image processing, and machine learning are evolving day by day. Many systems have been completely changed due to this evolve to achieve more accurate results. The attendance system is a typical example of this transition, starting from the traditional signature on a paper sheet to face recognition. This project proposes a method of developing a comprehensive embedded class attendance system using facial recognition with smart mirror The system is based on Raspberry Pi that runs Raspbian (Linux) Operating System installed on micro SD card. The Camera, as well as a smart mirror, are connected to the Raspberry Pi. By facing the camera, the camera will capture the image then pass it to the Raspberry Pi which is programmed to handle the face recognition by implementing the posture analyzing algorithm . If the student's input image matches with the trained dataset image then the attendance results will be stored in the MySQL database.