Objective: To determine the plasma proteomic profiling by using surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) combined with bioinformatics for screening biomarkers of endometriosis and primarily setting up a diagnostic model of endometriosis.Method.Thirty-six patients with endometriosis diagnosed laparoscopically and thirty-five healthy controls were included in the study.Their serum were analyzed by SELDI and protein chip to generate protein profiling spectra.Student t test was used to compare the peak intensifies of the protein profiling results from the different groups.Biomarker Pattern Software was used to analyze the data between two groups and set up a diagnostic model for endometriosis.Protein profiling spectra from sixteen endometriosis patients and fifteen healthy controls were used double-blindedly to test the efficiency of the diagnostic model and generate the sensitivity and specificity of the model.Result: Fourteen abnormally expressed protein peaks were detected in the plasma of patients with endometriosis (P＜0.01).The endometriosis diagnostic model was composed of three protein peaks.It correctly identified 33 of 36 patients with endometriosis and 29 of 35 controls in the training test.In the masked set 14 of 16 patients with endometriosis and 12 of 15 normal controls were correctly identified with sensitivity of 87.5% and specificity of 8o%.Conclusion: Patients with endometriosis have a unique cluster of proteins in plasma detected by SELDI.SELDI provides a new approach for screening novel biomarkers of endometriosis.Its utility in clinical practice need further study.