<p>A model to predict carpal tunnel syndrome (CTS) risk would improve ergonomic assessments and help reduce the incidence of occupational CTS and its associated costs. Research spanning over sixty years has shown that deviated wrist, forearm, and hand posture has on the hydrostatic pressure within the carpal tunnel (also known as carpal tunnel pressure, CTP). Elevated CTP is a mechanism of the development, or aggravation of CTS symptoms. The purpose of this thesis was to develop a model to predict CTS risk, based on CTP, and incorporate the model into an ergonomic tool for use by ergonomists. An extensive literature review identified additional studies that investigated the effects of pronation/supination, finger posture, and fingertip loading on CTP. The effect of wrist, forearm, and hand posture was then incorporated into the model via a series of regression equations developed for each plane of movement. The effect of fingertip loading (independent to the posture effects) was included using a multiplier based on the hand posture and load magnitude. To provide a user-friendly tool for ergonomists, a graphical-user-interface was developed to predict CTS risk based on the developed model. Input variables were wrist, hand, and forearm posture, and fingertip loading. CTP program estimated CTP, and compared the predicted pressure to a known threshold beyond which median nerve function has been shown to degrade. The tool was then evaluated by comparing the output of the tool (CTS risk) to the incidence of CTS in a large automotive manufacturing environment. There was no significant difference between the two groups (workers completing jobs with an incidence of CTS and workers completing jobs with no incidence of CTS). The tool marks an important first step v towards providing ergonomists with a much-needed tool to predict CTS risk based on posture, frequency, and fingertip force.</p> / Master of Science (MSc)