There is a high rate of inconformity between clinical staging and surgical-pathologic staging in endometrial cancer. Many patients with advanced endometrial cancer are preoperatively understaged and thereby do not receive the optimal therapy. Here, we aimed to develop a predictive model or biomarker for preoperative diagnosis of advanced endometrial cancer via multivariate logistic regression analysis. In this study, 259 eligible patients were included, and 195 patients were assigned to the training dataset and 64 patients to validation dataset. Age, menopause status, sterilization situation, parity, body mass index, hypertension, diabetes mellitus, tumor size, and ovarian malignancy algorithm (ROMA) index were included as predictive variables, and the binary outcome was advanced endometrial cancer or not. When the