Objective: To construct and validate a nomogram for prediction of in-hospital postoperative heart failure (PHF) in elderly patients with hip fracture. Methods: This was a retrospective cohort study. The patients aged ≥65 years undergoing hip fracture surgery in Peking University Third Hospital from July 2015 to December 2023 were enrolled. The patients admitted from July 2015 to December 2021 were divided into a development cohort, and the others admitted from January 2022 to December 2023 in to a validation cohort. The patients ' clinical data were collected from the electronic medical record system. Univariate and multivariate Logistic regression were employed to screen the predictors for PHF in the patients. The R software was used to construct a nomogram. Internal and external validation were performed by the Bootstrap method. The discriminatory ability of the model was determined by the area under the receiver operating characteristic curve (AUC). The calibration was evaluated by the calibration plot and Hosmer-Lemeshow goodness-of-fit test. Decision curve analysis (DCA) was performed to assess the clinical utility. Results: In the study, 944 patients were eventually enrolled in the development cohort, and 469 were in the validation cohort. A total of 54 (5.7%) patients developed PHF in the deve-lopment cohort, and 18 (3.8%) patients had PHF in the validation cohort. Compared with those from non-PHF group, the patients from PHF group were older, had higher prevalence of heart disease, hypertension and pulmonary disease, had poorer American Society of Anesthesiologists (ASA) classification (Ⅲ-Ⅳ), presented with lower preoperative hemoglobin level, lower left ventricular ejection fraction, higher preoperative serum creatinine, received hip arthroplasty and general anesthesia more frequently. Multivariate Logistic regression analysis showed that age (OR=1.071, 95%CI: 1.019-1.127, P=0.008), history of heart disease (OR=5.360, 95%CI: 2.808-10.234, P < 0.001), preoperative hemoglobin level (OR=0.979, 95%CI: 0.960-0.999, P=0.041), preoperative serum creatinine (OR=1.007, 95%CI: 1.001-1.013, P=0.015), hip arthroplasty (OR=2.513, 95%CI: 1.259-5.019, P=0.009), and general anesthesia (OR=2.024, 95%CI: 1.053-3.890, P=0.034) were the independent predictors for PHF in elderly patients with hip fracture. Four preoperative predictors were incorporated to construct a preoperative nomogram for PHF in the patients. The AUC values of the nomogram in internal and external validation were 0.818 (95%CI: 0.768-0.868) and 0.873 (95%CI: 0.805-0.929), indicating its good accuracy. The calibration plots and Hosmer-Lemeshow goodness-of-fit test (internal validation: χ²=9.958, P=0.354; external validation: χ²=5.477, P=0.791) showed its satisfactory calibration. Clinical usefulness of the nomogram was confirmed by decision curve analysis. Conclusion: An easy-to-use nomogram for prediction of in-hospital PHF in elderly patients with hip fracture is well developed. This preoperative risk assessment tool can effectively identify patients at high risk of PHF and may be useful for perioperative management optimization.