Models for predicting postoperative overall survival of patients with metaplastic breast cancer have not yet been discovered. The purpose of this study is to establish a model for predicting postoperative overall survival of metaplastic breast cancer patients. Patients in the Surveillance, Epidemiology, and End Results database diagnosed with MBC from 2010 to 2015 were selected and randomized into a SEER training cohort and an internal validation cohort. We identified independent prognostic factors after MBC surgery based on multivariate Cox regression analysis to construct nomograms. The discriminative and predictive power of the nomogram was assessed using Harrell's consistency index (C-index) and calibration plots. The decision curve analysis (DCA) was used to evaluate the clinical usefulness of the model. We verify the performance of the prediction model with a Chinese multi-center data set. Multifactorial analysis showed that age at diagnosis, T stage, N stage, M stage, tumor size, radiotherapy, and chemotherapy were important prognostic factors affecting OS. The C-index of nomogram was higher than the eighth edition of the AJCC TNM grading system in the SEER training set and validation set. The calibration chart showed that the survival rate predicted by the nomogram is close to the actual survival rate. It has also been verified in the SEER internal verification set and the Chinese multi-center data set. The prognostic model can accurately predict the post-surgical OS rate of patients with MBC and can provide a reference for doctors and patients to establish treatment plans.