Background: Heart failure (HF) has a high rate of mortality. It would be useful to have, at the time of a HF admission, a method of predicting post-discharge short-term mortality risk. Methods: We studied 947 Veterans hospitalized for HF at our VA medical center from January 2004 to December 2008, survived to discharge, had an ICD-9 code for HF as the primary discharge diagnosis, and had complete data for comorbidities, labs, medications and ECG findings. Mortality at 30-days post-discharge was determined and multivariable analyses identified independent predictors of mortality by logistic regression. These were used to develop a mortality risk score. Results: Mortality at 30-days occurred in 3.9% (37/947). Independent predictors (p-value <0.05) were substance abuse (OR = 3.10), abnormal admission serum sodium (OR=2.56), abnormal admission troponin (OR = 2.15), absence of dyslipidemia (OR = 2.04), not on a calcium channel blocker at admission (OR = 3.33), and not on an oral anticoagulant at admission (OR = 5.26). Each independent predictor was assigned 1-point and the resulting figure shows the rates of 30-day mortality to be 0.49%, 5.33% and 19.15% for those with risk scores of 0 to 2, 3 or 4, and ≥5, respectively. This represents a 39-fold difference in risk between the low-risk and high-risk patients. The c-statistic for the model was good (c = 0.796). Conclusions: Risk for post-discharge short-term mortality can be accurately predicted at the time of initial HF admission by a risk score employing admission labs, co-morbidities and medications. Patients identified as high risk at the time of admission might benefit from more intense inpatient evaluation and closer outpatient care.