The skeletal muscle system serves as the primary force-generating organ in the body, capable of rapidly changing shape and size in response to various stimuli. Different levels of bodily activity influence both the structure and function of these muscles. Inactivity can lead to muscle atrophy, while inappropriate exercise can result in fatigue, stiffness, and suboptimal muscle growth. To quantitatively assess the effects of exercise on the musculoskeletal system, an agent-based model of skeletal muscle can simulate how muscle fascicle cross-sectional area, directly linked to muscle fiber protein metabolism, responds to different exercise patterns and loading intensities (% of maximal voluntary contraction). This computational model has been utilized to examine the skeletal muscle system’s reactions to various body states, such as rest and different resistance training exercises. Previous studies on the effects of exercise on the musculoskeletal system focus on constructing the model without giving appropriate tools or guides to simulate the responses of skeletal muscle to different exercise patterns and loading intensities. This research introduces an agent-based model of skeletal muscle to investigate the influence of various exercise regimens and loading intensities on muscle fascicle cross-sectional area with the fundamental based on muscle fiber protein metabolism. The model simulates the physiological responses of individuals with knee osteoarthritis undergoing rehabilitation and those engaged in fitness training. This simulation tool has the potential to become a valuable tool for physiotherapists in designing and evaluating exercise programs effectively.