〔Abstract〕 Objective To evaluate the prognostic value of a radiomics model based on the peritumoral region of glioma. Methods 138 patients with glioma were retrospectively analyzed, medical imaging interaction toolkit(MITK) software was used to obtain the magnetic resonance imaging(MRI) images of peritumoral area 5 mm, 10 mm and 20 mm from the tumor edge and extract texture features. The texture features were screened the radiomics model was established and the radiomic score was calculated. A clinical prediction model and a combined prediction model along with Rad-score and clinical risk factors were established. The combined prediction model was displayed as a nomogram,and the predictive performance of the model for survival in glioma patients was evaluated.Results In the validation set,the C-index value of the radiomics model based on the peritumoral region 10 mm away from the tumor edge based on T2 weighted image( T2WI) images was 0. 663( 95% CI = 0. 72-0. 78),resulting in the best prediction performance. On the training set and validation set,the C-index of the nomogram was0. 770 and 0. 730,respectively,indicating that the prediction performance of nomogram was better than those of the radiomics model and clinical prediction model. The model had the highest prediction effect on the 3-year survival rate of glioma patients( training set area under curve( AUC) = 0. 93,95% CI = 0. 83-0. 98; validation set AUC= 0. 88,95% CI = 0. 76-0. 99). The calibration curve showed that the joint prediction nomogram in both the training set and the validation set had good performance. Conclusion The combined prediction model based on the preoperative T2WI images in the peritumoral region 10 mm from the tumor edge and the clinicopathological risk factors can accurately predict the prognosis of glioma,providing the best effect of prediction on the 3-year survival rate of glioma.