Aims The prognosis of heart failure (HF) depends on genetic predisposition, and recent studies have shown that impaired autophagy is involved in HF. This study was aimed to construct a prognostic model combining polygenetic background based on the autophagy pathway and other traditional risk factors (TRF) of HF prognosis. Methods and results Via re-analysing the transcriptomic data of 50 failing and 14 non-failing donors, differentially expressed autophagy-related genes (ARGs) were chosen for further comparison and analysis with whole exome sequencing and follow-up data of 1000 HF patients. By searching from reported articles, prognosis-related polymorphisms were identified. ARGs and prognosis-related polymorphisms were used to develop genetic risk score (GRS) and genetic risk factor (GRF), respectively. We compared the predictive power of five models [Model 1, GRS; Model 2, composite of TRF and N-terminal B-type natriuretic peptide (NT-proBNP); Model 3, composite of TRF, NT-proBNP, and GRS; Model 4, composite of TRF, NT-proBNP, and GRF; and Model 5, composite of TRF, NT-proBNP, GRF, and GRS] by applying receiver operating characteristic curves. Twenty-four prognosis-related polymorphisms were used to construct GRF and 11 variants among 48 differentially expressed ARGs associated with clinical outcomes of HF patients were applied for GRS. GRS was strongly associated with cardiac mortality of HF patients, independent of TRF and GRF (95% confidence interval 1.273-1.739, P = 5.78 x 10(-7)). Comparing with patients with lowest GRS tertile, those with highest tertile had higher risks of developing worse clinical outcomes (hazard ratio = 1.866; 95% confidence interval 1.352-2.575, P = 1.47 x 10(-4)). The discrimination power of the model including GRS, TRF, GRF, and NT-proBNP is most considerable (area under curve = 0.777), especially in men, patients over 60, patients with hypertension, patients without diabetes or hyperlipidaemia. Conclusions The model combining autophagy-related GRS, TRF, GRF, and NT-proBNP performs well in distinguishing between worse-prognosis and better-prognosis HF patients, leading a promising strategy for HF treatment and HF prevention.