This chapter presents an innovative attendance-tracking system that seamlessly merges RFID and facial detection technologies for automated monitoring in educational and professional environments. By utilizing RFID tags on identification cards, the system can swiftly identify individuals as they enter a location. Subsequently, facial recognition technology is employed to verify their identity by matching their faces with registered images. This dual-method approach significantly enhances the system’s accuracy and security while simultaneously reducing the need for manual attendance management efforts. Notably, the facial recognition component of the system employs a Support Vector Machine (SVM) as the training model. This choice of algorithm outperforms the Local Binary Pattern Histogram (LBPH) approach in terms of accuracy. The seamless integration of RFID and facial detection technologies results in an efficient, error-reduced attendance-tracking solution that is highly versatile and applicable across a wide range of settings. This system not only ensures precise attendance data but also offers an enhanced level of security, making it particularly valuable for educational institutions, corporations, and other professional environments seeking a streamlined and reliable attendance management solution.