This study was done to conduct a retrospective analysis and establish a clinical prediction model to predict individual survival outcomes of patients with small carcinomas of the breast. Based on the Surveillance, Epidemiology, and End Results (SEER) database, a total of 17,543 patients with small breast neoplasms diagnosed between 2013 and 2016 were analyzed to construct nomograms and predict 3-year, 5-year, and 10-year survival rates. This prognostic model provided a reasonable and effective method to predict the prognosis of patients with small breast cancer. Background: Different clinicopathologic characteristics could contribute to inconsistent prognoses of small breast neoplasms (T1a/T1b). This study was done to conduct a retrospective analysis and establish a clinical prediction model to predict individual survival outcomes of patients with small carcinomas of the breast. Materials and Methods: Based on the Surveillance, Epidemiology, and End Results (SEER) database, eligible patients with small breast carcinomas were analyzed. Univariate analysis and multivariate analysis were performed to clarify the indicators of overall survival. Pooling risk factors enabled nomograms to be constructed and further predicted 3-year, 5-year, and 10-year survival of patients with small breast cancer. The model was internally validated for discrimination and calibration. Results: A total of 17,543 patients with small breast neoplasms diagnosed between 2013 and 2016 were enrolled. Histologic grade, lymph node stage, estrogen receptor or progesterone receptor status, and molecular subtypes of breast cancer were regarded as the risk factors of prognosis in a Cox proportional hazards model (P <.05). A nomogram was constructed to give predictive accuracy toward individual survival rate of patients with small breast neoplasms. Conclusions: This prognostic model provided a robust and effective method to predict the prognosis of patients with small breast cancer. (C) 2020 Elsevier Inc. All rights reserved.