Background: Given the stable number of potential organ donors after brain death, donors after circulatory death have been an increasing source of organs procured for transplant. Among the most important considerations for donation after circulatory death (DCD) is the prediction that death will occur within a reasonable period of time after the withdrawal of cardiorespiratory support (WCRS). Accurate prediction of time to death is necessary for the procurement process. We aimed to develop simple predictive rules for death in less than 60 min and test the accuracy of these rules in a pool of potential DCD donors. Methods: A multicenter prospective longitudinal cohort design of DCD eligible patients (n=318), with the primary binary outcome being death in less than 60 min after withdrawal of cardiorespiratory support conducted in 28 accredited intensive care units (ICUs) in Australia. We used a random split-half method to produce two samples, first to develop the predictive classification rules and then to estimate accuracy in an independent sample. Results: The best classification model used only three simple classification rules to produce an overall efficiency of 0.79 (0.72-0.85), sensitivity of 0.82 (0.73-0.90), and a positive predictive value of 0.80 (0.70-0.87) in the independent sample. Using only intensive care unit specialist prediction (a single classification rule) produced comparable efficiency 0.80 (0.73-0.86), sensitivity 0.87 (0.78-0.93), and positive predictive value 0.78 (0.68-0.86). Conclusion: This best predictive model missed only 18% of all potential donors. A positive prediction would be incorrect on only 20% of occasions, meaning there is an acceptable level of lost opportunity costs involved in the unnecessary assembly of transplantation teams and theatres.