Abstract: Objective To explore the value of predicting endometriosis （EMT） associated malignant cancer based on the nomogram model. Methods 45 cases of patients with EMT- associated ovarian cancer and 312 cases of ovarian EMT cysts without malignant cancer were retrospectively selected from January 2015 to June 2020 in the First Affiliated Hospital of Hunan College of Traditional Chinese Medicine and underwent surgical treatment, according to weather was EMT carcinogenesis divided the research subjects into the cancerous group and non-cancerous group. Observed and recorded the general information, physical symptoms, laboratory examinations, and imaging examinations of the research subjects, and compared the difference between the two groups of patients. Logistic regression was used to determine the independent risk factors of malignant cancer, a nomogram prediction model was constructed, and receiver operating characteristic （ROC） was drawn to evaluate the predictive ability of the nomogram model. Results Human epididymal protein 4 （HE4）, ovarian cancer risk assessment index （Risk of Ovarian Malignancy Algorithm, ROMA）, solid components of the cyst, papilla of cyst wall, blood flow signal, cyst wall thickening, menopause, the maximum diameter of the cyst, age, menstrual abnormalities and course of EMT were the independent risk factors for malignant cancer. The nomogram model was constructed based on these risk factors and had a good fitting effect. The area under the ROC of the nomogram model was as high as 0.982, which meant the predictive ability was excellent. Conclusions HE4, a tumor marker of ovarian cancer, had a strong ability to predict malignant carcinogenesis of EMT. Ultrasound imaging examination also had a good auxiliary ability. The nomogram model constructed based on the independent risk factors found in this study can be used as a quantitative tool for the prediction of malignant cancer in EMT patients, which could be helpful for the formulation of preoperative treatment plans and improves the prognosis of patients.