The accurate prediction of overall survival (OS) is important in clinical decision-making for breast cancer treatment. We developed a model to predict the OS of non-metastatic breast cancer patients in China. This multicenter study included 1844 non-metastatic breast cancer patients who underwent breast cancer surgery between January 2009 and December 2011 in 3 tertiary teaching hospitals in China. Data were collected retrospectively from the database of each hospital. We used univariate and multivariate Cox proportional hazard regression analyses to screen for predictors. A nomogram was developed in the training cohort (from Sun Yat-sen Memorial Hospital [SYSMH]), externally validated in 2 validation cohorts (from the First People's Hospital of Foshan [FPHF] and Sun Yat-sen University Cancer Center (SYUCC)), and compared with CancerMath, a mathematical-based model. We used Receiver Operating Characteristic curves and calibration plots to assess the models. At median follow-ups of 65.9, 68.6, and 66.2 months, the 5-year OS rates were 93.0%, 86.7%, and 91.0% in the SYSMH, FPHF, and SYUCC cohorts, respectively. We identified age, T stage, lymph node status, estrogen receptor, and human epidermal growth factor receptor 2 statuses as significant prognostic factors. A nomogram was developed and externally validated in the FPHF (area under the curve = 0.74) and SYUCC (area under the curve = 0.77) cohorts. Calibration plots showed that the predicted OS was consistent with the actual OS. The nomogram outperformed CancerMath in our study population. In summary, we developed a nomogram to predict survival among non-metastatic breast cancer patientsin China. This nomogram is superior to the CancerMath model in Chinese populations.