Noninvasive risk stratification of patients who have suffered myocardial infarction (MI) is one of the greatest challenges in today's cardiology. No single test has sufficient predictive ability. Therefore, a combination of the tests must be applied for better post-MI risk stratification. The purpose of this study was to assess noninvasive predictors of 2 years cardiac mortality in post-MI patients and create a stratification model for identification of high-risk patients. Clinical, electrocardiographic, and echocardiographic parameters were evaluated before hospital discharge in 180 survivors of acute MI (mean age 57.0 +/- 9.9, male 82.2%), followed up for 2 years. A multivariate logistic regression analysis was used to determine informative predictors of cardiac mortality. A clinical score was constructed using the regression coefficient from the multivariate model. During follow-up, 16 deaths (8.8%) occurred. Multivariate analysis identified a combination of six variables that showed the strongest association with cardiac mortality. Based on the coefficients of the logistic regression, six variables were used to create a scoring system: filtered QRS duration (QRSd) >114 ms, coefficient of variation (Cv) <or=2.5%, maximal corrected QT interval (QTcmax) >or=445 ms, left ventricular ejection fraction (LVEF) <or=30%, the absence of use of beta-blockers (BB), and absence of treatment by primary percutaneous coronary intervention (PCI). The cutoff value for the score of 10 or higher, defined the "high-risk" patients with a sensitivity of 75% and a specificity of 70%. The mortality rate for the low- and high-risk groups were 12.5% and 87.5%, respectively. The receiver operating characteristic (ROC) analysis yielded area under curve of 0.88. The proposed scoring system could be valuable in predicting 2 years risk of cardiac mortality in post-MI population and allows the stratification of patients into low- and high-risk groups.