Global outcome measures that are widely used in stroke clinical trials, such as the modified Rankin Scale (mRS), lack sufficient detail to detect changes within specific domains (e.g., sensory, motor, visual, linguistic, or cognitive function). Yet such data are vital for understanding stroke recovery and its mechanisms. Poststroke deficits in specific domains differ in their rate and degree of recovery and in their effects on overall independence and quality of life. For example, even in a patient with complete recovery of strength, persistent deficits in the nonmotor domains such as language and cognition may make a return to independent living impossible. In such cases, global measures based solely on the patient’s degree of independence would overlook a complete recovery in the motor domain. Capturing these important aspects of recovery demands a domain-specific approach. If stroke outcomes trials are to incorporate finer-grained recovery metrics—which can require substantial time, effort, and expertise to implement—efficiency must be a priority. In this article, we discuss how commonly collected clinical data from the NIH Stroke Scale can guide the judicious selection of relevant recovery domains for more detailed testing. Our overarching goal is to make the implementation of domain-specific testing more feasible for large-scale clinical trials on stroke recovery.