Age-related decline in physical and neural capacity can make the sit-to-stand (STS) motion increasingly difficult for older adults, significantly impacting their quality of life. Despite these declines, humans adopt compensatory movement strategies to mitigate the effects of reduced capacity, maintaining functional mobility. Predictive simulations offer a tool for studying the relationship between capacity decline and compensation strategies. However, previous predictive studies have omitted the modeling and control of arm movements, thus neglecting key arm compensation strategies relevant to the STS motion. Therefore, this study aimed to develop a neuromuscular controller for a three-dimensional musculoskeletal model that includes the arms, enabling the simulation of STS arm compensation strategies. STS arm strategies were successfully simulated and displayed comparable joint kinematics with experimental data. However, the simulations revealed elevated leg muscle activations and an overestimated vertical ground reaction force. Additional simulations with changed conditions demonstrated the effective use of the armrest and thigh push-off strategies to adapt to lower seat heights and reduce peak knee joint load. Overall, the neuromuscular controller in this study provides a new basis for future STS research into uncovering the link between capacity decline and compensation strategies, potentially leading to improved methods for assessing and addressing age-related declines in crucial movements.