Risk stratification models are effective tools for the management of cardiovascular diseases. Although several risk scores have been proposed, the relevance and superiority of these predictive models have not been fully validated in an independent and nonclinical trial-based population. We studied 2,472 consecutive patients initially hospitalized in our institution from April 2004 to December 2009. Risk scores were calculated for each patient using 4 risk score models, including the Seattle Heart Failure Model (SHFM), Acute Decompensated Heart Failure National Registry regression model, the American Heart Association Get With The Guidelines-Heart Failure score, and the Association of Health Aging and Body Composition Heart Failure score. The predictive ability for the composite end point, including total death, heart transplantation, and left ventricle assist device implantation, was assessed by calculating the area under the receiver operating characteristic curve for each model. During the follow-up period after admission (median 924.5 days), the combined end point occurred in 295 patients (11.8%), including 27 in-hospital deaths (1.1%). Compared with the other 3 risk score models, the SHFM risk score demonstrated a greater area under the curve for the combined end point at the overall, in-hospital, 30-day, and 1-, 2-, and 3-year follow-up point (0.741 to 0.890). The survival rate predicted by SHFM demonstrated an excellent correlation with the actual survival rate (R2 = 0.990). In conclusion, these results suggest that the SHFM risk score is the most suitable for the discrimination and calibration of mortality risk stratification in patients with cardiovascular disease.