Abstract: The upper limb extends from the shoulder to the hand, and includes the shoulder, elbow, forearm, and wrist joints, as well as an additional 15 joints in the fingers and thumb. Completion of activities of daily living often involves postural changes at multiple joints simultaneously, and the challenge of coordinating functional movements is further complicated by the fact that many of the muscles in the upper limb cross and actuate multiple degrees of freedom. Biomechanical modeling, together with both static and dynamic simulation techniques, plays a critical role in the advancement of our understanding of function in the upper limb, with and without impairment. There are important challenges associated with simulating hand and arm movements, including the fact that the typical, functional movements performed using the upper limb are not cyclic and tend to be less stereotyped compared to the types of motions (e.g., gait) for which many popular simulation methodologies have been developed. Similarly, a relative paucity of applicable experimental data can slow the development of effective simulation studies, as interested biomechanists must often also simultaneously design the experimental studies needed in order to have any data to which they can compare their results. Overall, general scientific skepticism of conclusions drawn from simulation studies is a major challenge for simulation of any type of human movement. Despite these challenges, the advances in the field of biomechanical simulation present important opportunities for improving our understanding of neuromuscular control, impairment, and rehabilitation of the human upper limb. Especially considering the complexity and diversity of the types of movements we complete, insights derived from biomechanical simulation studies can provide focus. In my laboratory, the quantitative anatomy embedded in our models has helped us to generate new hypotheses and better define the experimental studies needed to test them, given the complexity of the system being tested. Similarly, we regularly use model-based approaches to integrate experimental results from multiple sources, broadening our overall understanding of the data. This last piece has proven especially important in translation of our research to clinicians. In general, modeling and simulation provide an important opportunity to advance the types of questions we can ask about upper limb function.