Background: identifying heart failure (HF) patients most at-risk of readmission permits targeting adapted interventions. The use of administrative data enables regulators to support the implementation of such interventions. Methods and results: in a French nationwide cohort of patients aged 65 years or older surviving an index hospitalization for HF in 2015 (N = 70 657), we studied HF readmission predictors available in administrative data, distinguishing HF severity from overall morbidity and taking into account the competing mortality risk, over a 1-year follow-up period. We also computed cumulative incidences and daily rates of HF readmission for patient groups defined upon HF severity and overall morbidity. 31.8% (n = 22 475) of patients were readmitted at least once for HF and 17.6% (n = 12 416) died without any HF readmission. HF severity and overall morbidity were the strongest HF readmission predictors (subdistibution Hazard Ratios 2.66 [95% CI: 2.52-2.81] and 1.37 [1.30-1.45] respectively, when comparing extreme categories). Overall morbidity and age were more strongly associated with the competing rate of death without HF readmission (cause-specific Hazard Ratios). Defined risk-groups had approximately 40% of separation in HF readmission proportion (21.9%, n = 2 144/9 786 versus 60.4%, n = 618/0 1023). Conclusions: segmentation of HF patients into readmission risk-groups is possible using administrative data and enables targeting of preventive interventions.