Abdominal aortic aneurysm rupture is known to have high operative mortality. It is, therefore, imperative to unravel risk factors affecting mortality and to develop a model for outcome prediction. The aim of this study was to develop a model for prediction of operative mortality in ruptured abdominal aortic aneurysms, by combining statistical and data mining methods. Variables potentially affecting mortality were investigated by retrospective analysis of medical records of patients operated due to the aortic aneurysm rupture between 1996. and 2010. in clinical Hospital Center Zagreb. Two novel models of operative mortality have been developed, with better discriminatory power then the previously published ones on our patient sample. Hints of other potentially relevant variables have also been discovered. A simple preoperative prediction model, containing only two variables ("Age", "Loss of consciousness") was shown to have good discriminatory ability on prospective validation. We consider it to be a good model for clinical usage in our institution, as well as a good starting point for developing a national prediction model. Integration of data mining with medical statistics also represents a methodological advancement in the domain of ruptured aortic aneurysms and in similar fields. Results of this study could improve the quality control process, reporting standardization, rational health resource utilisation, and, hopefully, unravel new, potentially correctible factors affecting operative mortality.