Objective To construct a radiomic risk model to predict the risk of epileptic seizures in patients with diffuse low-grade glioma (DLGG) and to preliminatively assess patient outcomes. Materials and Methods Using the imaging datasets and clinical data provided by TCGA and TCIA databases, an epilepsy risk score model was constructed by radiomics methods. Further nomograms were established based on the model combined with clinical indicators to predict the probability of epilepsy and the probability of long-term survival. Receiver operator characteristic curve and decision curve analysis were used to evaluate the predictive effectiveness of predictive models. Results In this study, 10 radiomic features were filtered out to establish the epilepsy risk scoring model. The AUC values of internal verification and external verification were 0.900 and 0.636, respectively. The positive rate of epilepsy in high-risk group and low-risk group were 80.6% and 27.3%, respectively. There was significant difference in 5-year OS between the high-risk and low-risk groups (P=0.029). DCA showed that the net benefit rate of the image-clinical model was higher than that of the clinical prediction model. The calibration curve showed that the 3-year, 5-year survival nomogram had good calibration and differentiation ability and the 5-year survival of the high risk group and low risk group in the nomogram had significant difference (P=0.008). Conclusions:In this study, a radiomic model based on preoperative multimodal MRI of DLGG was established for non-invasive prediction of the risk of associated epilepsy and prognosis, which provides a reference for the individualized treatment strategies.