Abstract Aims The applicability of currently available risk prediction models for patients undergoing percutaneous coronary interventions (PCIs) is limited. We aimed to develop a model for the prediction of in-hospital mortality after PCI that is based on contemporary and representative data from a European perspective. Methods and results Our analyses are based on the Euro Heart Survey of PCIs, which contains information on 46 064 consecutive patients who underwent PCI for different indications in 176 participating European centres during 2005–08. Patients were randomly divided into a training (n = 23 032) and a validation (n = 23 032) set with similar characteristics. In these sets, 339 (1.5%) and 305 (1.3%) patients died during hospitalization, respectively. On the basis of the training set, a logistic model was constructed that related 16 independent patient or lesion characteristics with mortality, including PCI indication, advanced age, haemodynamic instability, multivessel disease, and proximal LAD disease. In both the training and validation data sets, the model had a good performance in terms of discrimination (C-index 0.91 and 0.90, respectively) and calibration (Hosmer–Lemeshow P-value 0.39 and 0.18, respectively). Conclusion In-hospital mortality in PCI patients was well predicted by a risk score that contains 16 factors. The score has strong applicability for European practices.