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Classroom attendance tracking was a fundamental task in educational institutions, traditionally managed throughmanual roll calls or sign-in sheets. These methods were time-consuming, error-prone, and susceptible to manipulation. Withadvancements in computer vision and embedded systems, there was an opportunity to automate this process. In this researchpaper, a novel approach to classroom attendance management was presented, utilizing OpenCV and face recognitiontechnologies, implemented on the ESP32-CAM microcontroller. The proposed system was designed to automatically identify andrecord student attendance, offering enhanced accuracy and efficiency. Comparative results demonstrated that the facerecognition-based approach significantly outperformed traditional manual methods and other automated systems in terms ofaccuracy and processing speed. The system's architecture, implementation, and evaluation were outlined, showcasing itspotential to transform attendance tracking in educational settings.