Regular exercise is vital for achieving both physical and mental well-being. This study proposed a real-time system that monitors and counts biceps curl repetitions based on an individual’s fitness history. The system utilizes advanced pose estimation technologies, including Blaze Pose and Move Net, to pinpoint key body landmarks such as the shoulders, elbows, and wrists. These landmarks are used to calculate joint angles and evaluate exercise patterns. A comparative analysis demonstrated that Blaze Pose achieved an accuracy of 98.54%, exceeding Move Net’s accuracy of 97.81%, and was selected as the most effective model for this application. By providing immediate feedback on workout intensity and tracking progress over time, the system empowers users of all fitness levels to improve their exercise routines and achieve their health goals.