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The Smart Attendance System using Face Recognition is a computer-vision-based solution developed to automate attendance marking through a laptop camera. The project addresses common difficulties associated with manual registers, identification cards, and touch-based biometric methods, including time consumption, human errors, duplicate entries, and proxy attendance. The implemented system is developed in Python and uses OpenCV and a face-recognition library to process live video. Facial images of authorized users are registered first and converted into numerical facial encodings. During operation, frames from the laptop camera are resized for faster processing, faces are detected, and the resulting encodings are compared with stored encodings using Euclidean Distance. When a valid match is obtained, the attendance module records the recognized name with the current date and time in an Excel sheet and checks previous entries to avoid duplicate marking. Testing of the working model showed successful face detection and recognition under normal operating conditions, responsive live processing after image downscaling, and immediate digital attendance updating. The prototype therefore demonstrates a practical, contactless, and low-additional-hardware approach for attendance management in educational and organizational environments. Key Words: Face recognition, smart attendance, computer vision, facial encoding, Euclidean Distance, OpenCV.