Objective To evaluate the performance of the Chinese system for cardiac operative risk evaluation (SinoSCORE) in predicting the in-hospital mortality and postoperative complications in patients undergoing cardiac valve surgery. Methods The clinical data of patients undergoing valve surgery in Changhai Hospital between 2005 and 2011 were retrospectively analyzed. SinoSCORE was used to calculate the in-hospital mortality risk. The relationship of SinoSCORE result with postoperative complications (low cardiac output syndrome, renal failure, lung infection, application of intra-aortic balloon pump \[IABP\] , prolonged ventilation, prolonged postoperative ICU stay and reoperation) was verified. Discrimination degree of the model was tested by determining the area under the receiver operating characteristic (ROC) curve, and calibration of the model was evaluated by Hosmer-Lemeshow goodness-of-fit test. The optimal cut-off points for postoperative complications, which could be well predicted by SinoSCORE, were obtained by Youden index. Results The mean age of the 3 407 enrolled patients was (49.2±13.3) years. The area under ROC was 0.754 (95%CI: 0.701-0.806), indicating good discrimination power of the model in predicting in-hospital mortality. The overall in-hospital mortality was 3.05%(104/3 407). The predicted in-hospital mortality by SinoSCORE was (3.1±0.1)%. Hosmer-Lemeshow calibration test yielded χ²=9.454，P=0.490, suggesting a high calibration ability of the model. The areas under ROC of low cardiac output syndrome, renal failure, and application of IABP were 0.708, 0.711, and 0.718, respectively, suggesting that SinoSCORE had a satisfactory performance in predicting post-operative low cardiac output syndrome, renal failure, and application of IABP. And the optimal cut-off points for the above three complications predicted by SinoSCORE were 5.5, 7.5, and 6.0, respectively. Conclusion SinoSCORE has a better performance in predicting the in-hospital mortality risk in Chinese patients undergoing valve surgery, and it can better predict post-operative low cardiac output syndrome, renal failure, and application of IABP.