Background: The assessment of risk at the time of discharge could be a useful tool for guiding post-discharge management. The aim of this study was to develop a novel and simple assessment tool for the better hospital discharge risk stratification. Methods: Between Nov 2005 and Aug 2007, 4,635 hospital discharge patients with acute myocardial infarction (62.6짹 12.5 years, 71.0% males) were enrolled in a nationwide prospective Korea Acute Myocardial Infarction Registry (KAMIR). We added several risk factors for variables such as stroke or peripheral artery disease history, admission hyperglycemia and left ventricular systolic dysfunction. 4,353 (94%) patients were performed echocardiogram at the time of presentation, and left ventricular ejection fraction (LVEF) was checked in all patients. New risk score was constructed using the 6 independent variables related to the primary end point by utilizing a multivariable Cox regression analysis: Age (65 - 74 : 1 point, > 75 : 2 points), Killip class (II : 1 point, III, IV : 2 points), serum creatinine (��� 1.5 mg/dL : 1 point), no in-hospital percutaneous coronary intervention (1 point), LVEF < 40% (1 point) and admission glucose (��� 180 mg/dL: 1 point) based on the multivariate–adjusted risk relationship. New risk score system was compared with the Global Registry of Acute Coronary Events (GRACE) postdischarge risk model for during 12-month clinical follow-up. Results: During one-year follow-up, all cause of death occurred in 247 patients (5.3%). The accuracy for one year mortality by GRACE and new risk score system was 0.77 area under the curve (AUC) (CI: 0.74 – 0.80) and 0.83 (CI: 0.80-0.86) respectively. A significant difference is existed (0.77 vs. 0.83, p<0.0001). New risk score (AUC: 0.79; CI: 0.75 – 0.83) demonstrated a significant differences in predictive accuracy when compared with GRACE (0.79 vs. 0.73, p=0.0007) for STEMI, and also for NSTEMI (0.86 vs. 0.81, p = 0.0079). Conclusion: The new risk score system for AMI patients is a simple and better risk scoring system than GRACE hospital discharge risk model in the prediction of one-year mortality.