This project is to construct a face recognition-based attendance monitoring system for various educational institutions for taking attendance of students accurately. Previously attendance was taken manually where the professor/ teacher used to record attendance of students in log registers. This process is time-consuming and hectic. The professor/teacher might miss marking the attendance for few students or an illegal third party might manipulate the log register. The accuracy and security were at stake always. Then there was a new attendance system using fingerprints. This system might be accurate but there is a chance of stealing fingerprints from the biometric device for malicious activities. In this project, we use the face which is the most important part of our body. The facial features of individuals are recognized and analyzed for taking attendance. In this project, we use one of the most popular programming languages Python, and its library called OpenCV which is used to capture live images and videos. The face images and details like registration number and name of the student will be saved in files and attendance notes can be seen in Excel Spreadsheet. The image detection and processing are done using the LBPH algorithm which is known for its simple yet efficient performance.