Background: The breast cancer surgical risk calculator (BCSRc) is a prognostic tool that determines a breast cancer patient’s unique risk of acute complications following each possible surgical intervention. When used in the preoperative setting, it can help to stratify patients with an increased complication risk and enhance the patient-physician informed decision-making process. The objective of this study was to externally validate the four models used in the BCSRc on a large cohort of patients who underwent breast cancer surgery. Methods: The BCSRc was developed by using a retrospective cohort from the National Surgical Quality Improvement Program database from 2005 to 2018. Four models were built by using logistic regression methods to predict the following composite outcomes: overall, infectious, hematologic, and internal organ complications. This study obtained a new cohort of patients from the National Surgical Quality Improvement Program by utilizing participant user files from 2019 to 2020. The area under the curve, brier score, and Hosmer-Lemeshow goodness of fit test measured model performance, accuracy, and calibration, respectively. Results: A total of 192,095 patients met inclusion criteria in the development of the BCSRc, and the validation cohort included 60,144 women. The area under the curve during external validation for each model was approximately 0.70. Accuracy, or Brier scores, were all between 0.04 and 0.003. Model calibration using the Hosmer-Lemeshow statistic found all p-values > 0.05. All of these model coefficients will be updated on the web-based BCSRc platform: www.breastcalc.org . Conclusions: The BCSRc continues to show excellent external-validation measures. Collectively, this prognostic tool can enhance the decision-making process, help stratify patients with an increased complication risk, and improve expectant management.