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Objectives. ere have been no fully validated tools for the rapid identification of surgical patients at risk of intraoperative hypothermia. e objective of this study was to validate the performance of a previously established prediction model in estimating the risk of intraoperative hypothermia in a prospective cohort. Methods. In this observational study, consecutive adults scheduled for elective surgery under general anesthesia were enrolled prospectively at a tertiary hospital between September 4, 2020, and December 28, 2020. An intraoperative hypothermia risk score was calculated by a mobile application of the prediction model. A wireless axillary thermometer was used to continuously measure perioperative core temperature as the reference standard. e discrimination and calibration of the model were assessed, using the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow goodness-of-fit test, and Brier score. Results. Among 227 participants, 99 (43.6%) developed intraoperative hypothermia, and 10 (4.6%) received intraoperative active warming with forced-air warming. e model had an AUC of 0.700 (95% confidence interval [CI], 0.632-0.768) in the overall cohort with adequate calibration (Hosmer-Lemeshow χ 2 � 13.8, P � 0.087; Brier score � 0.33 [95% CI, 0.29-0.37]). We categorized the risk scores into low-risk, moderate-risk, and highrisk groups, in which the incidence of intraoperative hypothermia was 23.0% (95% CI, 43.4% (95% CI,2), and 62.7% (95% CI, 51.5-74.3), respectively (P for trend <0.001). Conclusions. e intraoperative hypothermia prediction model demonstrated possibly helpful discrimination and adequate calibration in our prospective validation. ese findings suggest that the risk screening model could facilitate future perioperative temperature management.