Abstract: Background　Male breast cancer (MBC) is clinically rare; however, its annual occurrence rate has increased in recent years. Currently, there is almost no prospective data to guide the clinical management of MBC, and treatment strategies are primarily extrapolated from those for female breast cancer.Objective　To develop a clinical prediction model for prognosis in male breast cancer patients and externally validate it using data from MBC patients at our institution.Methods　Patients with MBC from the SEER database from 1990 to 2019 were selected and randomly divided into a training set and a validation set at a ratio of 7:3. The overall 5-year death of MBC patients was used as the outcome indicator. Lasso regression, univariate, and multivariate Cox proportional hazards models were employed to screen for predictive features. The discriminative ability and calibration of the clinical prediction model were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and external validation analysis. A nomogram was constructed to visualize the clinical prediction model.Results　This study included 1 614 patients from the SEER database as the study subjects and divided them into a training set (n=1 129) and a validation set (n=485). Follow-up results showed that 274 and 111 patients died in the training set and the validation set, respectively. LASSO regression identified 9 clinical features: age at diagnosis, histological grade, T stage, N stage, M stage, bone metastasis status, surgical intervention status, estrogen receptor (ER) status, and progesterone receptor (PR) status. Univariate Cox proportional hazards model analysis revealed that all variables were significantly associated with risk of death in MBC (P < 0.05). Multivariate Cox proportional hazards model analysis demonstrated that age, tumor grade, T stage, N stage, M stage, and bone metastasis were independent risk factors for risk of death. At the same time, surgical intervention, ER positivity, and PR positivity served as protective factors (P <0.05). In the development set, the AUC values for the 1-, 3-, and 5-year risk of death prediction models were 0.895, 0.853, and 0.829, respectively, with a C-index of 0.811. In the validation set, the corresponding AUC values were 0.858, 0.858, and 0.848, with a C-index of 0.798. External validation was performed on 44 patients with MBC in our hospital. The AUC for 5-year risk of death was 0.731, and the 10-year risk of death was 0.797.Conclusion　This study establishes a prediction model based on diagnostic age, histological grading, T staging, N staging, M staging, bone metastasis status, surgical intervention status, ER status, and PR status, which has high predictive value for risk of death in MBC patients and provides a reliable tool for clinical doctors.