The lack of quantifiable, reliable and repeatable methods for assessing functional capabilities of users with physical limitations creates challenges for accessibility researchers and practitioners. Current practice includes descriptors such as medical diagnoses, third-party observations, and self-assessment to characterize physical capabilities of information technology users. These solutions are inadequate due to similarities in functional capabilities between diagnoses, differences in capabilities within a diagnosis, and the potential for bias when characterizing functional capabilities. The current research examines performance-based functional assessment as an alternative to existing assessment techniques. Initial study results based on a single focus model (task efficiency) were reported earlier [1, 2]. This paper builds on that work, highlighting the benefits of integrating multiple perspectives such that both efficiency and anomalies are considered. A decision tree was produced combining results from several performance-based functional assessment models providing improved predictive capabilities.