Hip fractures are common in patients of advanced age and are associated with excess mortality. Rapid and accurate prediction of the prognosis using information that can be easily obtained before surgery would be advantageous to clinical management. We performed a population-based retrospective cohort study using an 8.5-year Japanese claims database (April 2012-September 2020) to develop and validate a predictive model for long-term mortality after hip fracture. The study included 43,529 patients (34,499 [79.3%] women) aged ≥65 years with first-onset hip fracture. During the observation period, 43% of the patients died. Cox regression analysis identified the following prognostic predictors: sex, age, fracture site, nursing care certification, and several comorbidities (any malignancy, renal disease, congestive heart failure, chronic pulmonary disease, liver disease, metastatic solid tumor, and deficiency anemia). We then developed a scoring system called the Shizuoka Hip Fracture Prognostic Score (SHiPS); this system was established by scoring based on each hazard ratio and classifying the degree of mortality risk into four categories based on decision tree analysis. The area under the receiver operating characteristic (ROC) curve (AUC) (95% confidence interval [CI]) of 1-year, 3-year, and 5-year mortality based on the SHiPS was 0.718 (95% CI, 0.706-0.729), 0.736 (95% CI, 0.728-0.745), and 0.758 (95% CI, 0.747-0.769), respectively, indicating good predictive performance of the SHiPS for as long as 5 years after fracture onset. Even when the SHiPS was individually applied to patients with or without surgery after fracture, the prediction performance by the AUC was >0.7. These results indicate that the SHiPS can predict long-term mortality using preoperative information regardless of whether surgery is performed after hip fracture.