Objective To develop a logistic regression model for differential diagnosis of the malignant ovarian tumor by combining transvaginal conventional ultrasonography and 3D power Doppler ultrasound(3D-PDUS) techniques. Methods The transvaginal ultrasonography and 3D-PDUS data were collected from 291 patients with ovarian tumors received clinical pathological diagnosis.According to the pathological resuts,the 291 patients were divided in to benign group(GB) and borderline/malignant group (GM). Univariate and multivariate logistic regression analyses were applied to establish models for predicting malignant tumor. Results ① Within the 291 ovarian tumor patients,175 (60.14% ) were classified as the GB and 116 (39.86% ) were considered as the GM,the number for postmenopausal cases and the serum CA125 level in GB group were significantly lower than those in GM group ( P <0.001); ②The tansvaginal conventional ultrasound analysis suggested that borderline/malignant tumor often presented as larger volume,more irregular shape,and higher incidence in the blood flow within a solid papillary projection and ascites (P< 0.05,compared with GB group);In 3D-PDSU data,the vascularization index (VI) was lower than that in GB group( P <0.001,compared with GM group),but there was no significant difference between GB group and GM group in flow index (FI) and vascularization-flow index (VFI) ( P =0.559,0.454); ③ Multivariate logistic regression analysis showed that postmenopausal status,serum CA125 levels,tumor echo,papillary with blood flow,ascites and 3D-PDUS VI parameters were independent risk factors for the progression of borderline/malignant tumor.The ROC curve showed that the established regression model accuracy was 92.0%,sensitivity was 86.2%,specificity was 95.7%,positive predictive value was 92.6% and negative predictive value was 91.7%. Conclusions Combining multi-model transvaginal conventional ultrasound and 3D-PDUS analyses is a useful non-invasive technique for the differential diagnosis of ovarian tumor.