Using quick facial recognition to enable smart attendance is a practical way to manage everyday tasks and keep track of student attendance. Face biometrics, based on high-resolution monitor footage and other technologies, is used by face recognition-based attendance systems to identify students by their faces. In this study, we designed and implemented a machine learning-based facial recognition academic attendance system, aiming to improve the efficiency and accuracy of attendance management in educational institutions. The system automatically recognizes student attendance by utilizing efficient facial recognition technology, thereby reducing the labour cost and time consumption of traditional attendance methods. Firstly, we collected and Firstly, we collected and preprocessed a large amount of facial data, and trained a high-precision facial recognition model using deep learning algorithms. Subsequently, the model was integrated into a user-friendly attendance management system. Model was integrated into a user-friendly attendance system, supporting real-time attendance recording and data management. The system test results show that our facial recognition model has achieved excellent performance in accuracy and recognition speed.