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Background: Donation after circulatory death (DCD) is a procedure in which after planned withdrawal of life-sustaining treatment (WLST), the dying process is monitored. A DCD procedure can only be continued if the potential organ donor dies shortly after WLST. This study performed an external validation of 2 existing prediction models to identify potentially DCD candidates, using one of the largest cohorts., Methods: This multicenter retrospective study analyzed all patients eligible for DCD donation from 2010 to 2015. The first model (DCD-N score) assigned points for absence of neurological reflexes and oxygenation index. The second model, a linear prediction model (LPDCD), yielded the probability of death within 60 min. This study determined discrimination (c-statistic) and calibration (Hosmer and Lemeshow test) for both models., Results: This study included 394 patients, 283 (72%) died within 60 min after WLST. The DCD-N score had a c-statistic of 0.77 (95% confidence intervals, 0.71-0.83) and the LPDCD model 0.75 (95% confidence intervals, 0.68-0.81). Calibration of the LPDCD 60-min model proved to be poor (Hosmer and Lemeshow test, P < 0.001)., Conclusions: The DCD-N score and the LPDCD model showed good discrimination but poor calibration for predicting the probability of death within 60 min. Construction of a new prediction model on a large data set is needed to obtain better calibration., Competing Interests: The authors declare no funding or conflicts of interest., (Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc.)