Background: Using data from different health centers can provide more accurate knowledge of the survival prognostic factors and their effect on the patient’s survival. In this multicenter study, we aimed to investigate the role of prognostic factors on breast cancer survival with large data set. Methods: This historical cohort study was carried out using data from 1785 participants with breast cancer. Data were gathered from medical records of patients referring to 4 breast cancer research centers in Tehran, Iran, between 1997 and 2013. Age at diagnosis (year), size of the tumor, involve lymph nodes, tumor grade, type of surgery, auxiliary treatment of chemotherapy, radiotherapy, recurrence, and metastasis were the prognosis factors considered in this study. A shared frailty model with a gamma distribution for frailty term was used. Results: The median follow-up period was 29.71 months with the interquartile range of 19 to 61 months. During the follow-up period, 337 (18.9%) patients died from breast cancer and 1448 (81.1%) survived. The 1-, 3-, 5-, and 10-year survival rates were 96%, 84%, 76%, and 58%, respectively. In the Cox model by centers, in Center A, the type of surgery, number of nodes involved, and the grade 3 tumor; in center B, age, radiotherapy, metastasis, and between 1 and 3 involved nodes; in center C, age, radiotherapy, recurrence, metastasis, tumor size, and grade 3 tumor; and in center D, chemotherapy, metastasis, and lymph nodes involved were significant. Shared frailty model showed that type of surgery, number of lymph nodes involved, metastasis, radiotherapy, and the tumor grade are the prognostic factors survival in breast cancer. The frailty variance was significant, and it affirmed there was significant variability between centers. Conclusions: This study showed it is necessary to consider the frailty term in modeling multicenter survival studies and confirmed the importance of early diagnosis of cancer before the involvement of lymph nodes and the onset of metastasis and timely treatment could lead to longer life and increased quality of life for patients.