The thermoregulatory sweat test (TST) can be central to the identification and management of disorders affecting sudomotor function and small sensory and autonomic nerve fibers, but the cumbersome nature of the standard testing protocol has prevented its widespread adoption. A high-resolution, quantitative, clean and simple assay of sweating could significantly improve identification and management of these disorders. Images from 89 clinical TSTs were analyzed retrospectively using two novel techniques. First, using the standard indicator powder, skin surface sweat distributions were determined algorithmically for each patient. Second, a fundamentally novel method using thermal imaging of forced evaporative cooling was evaluated through comparison with the standard technique. Correlation and receiver operating characteristic analyses were used to determine the degree of match between these methods, and the potential limits of thermal imaging were examined through cumulative analysis of all studied patients. Algorithmic encoding of sweating and nonsweating regions produces a more objective analysis for clinical decision-making. Additionally, results from the forced cooling method correspond well with those from indicator powder imaging, with a correlation across spatial regions of -0.78 (confidence interval: -0.84 to -0.71). The method works similarly across body regions, and frame-by-frame analysis suggests the ability to identify sweating regions within ~1 s of imaging. Although algorithmic encoding can enhance the standard sweat testing protocol, thermal imaging with forced evaporative cooling can dramatically improve the TST by making it less time consuming and more patient friendly than the current approach. NEW & NOTEWORTHY The thermoregulatory sweat test (TST) can be central to the identification and management of several common neurological disorders, but the cumbersome nature of the standard testing protocol has prevented its widespread adoption. In this study, images from 89 clinical TSTs were analyzed retrospectively using two novel techniques. Our results suggest that these improved methods could make sweat testing more reliable and acceptable for screening and management of a range of neurological disorders.