Objective To investigate the nutritional status of cancer patients undergoing radiotherapy using the Global Leadership Initiative on Malnutrition GLIM criteria and establish a predictive model for post-radiotherapy nutritional deterioration. Method A total of 97 hospitalized cancer patients who received radiotherapy at the Fourth Military Medical University of the Chinese People′s Liberation Army from January 2022 to December 2022 were selected. The GLIM criteria for malnutrition were applied before radiotherapy and patients were categorized into stable nutrition n = 57 or deteriorated nutrition groups n = 40 based on whether they experienced more than a 5% body weight loss after radiotherapy. Univariate and multivariate Logistic regression analysis was conducted to identify factors influencing nutritional deterioration during hospitalization and a nomogram prediction model was developed based on these factors. Discrimination AUC Hosmer-Lemeshow test and decision curve analysis DCA were used to assess the model′s accuracy and clinical utility. Result Among the 97 patients 38 39. 1% had nutritional risk or malnutrition while 40 41. 2% experienced nutritional deterioration following radiotherapy. There were no significant differences in age gender education level tumor location underlying diseases distant metastasis or BMI at admission between the two groups. Univariate and multivariate logistic regression analyses revealed that GLIM malnutrition status radiotherapy frequency and prealbumin levels independently predicted nutritional deterioration after radiotherapy P < 0. 05 . The nomogram model demonstrated an AUC value of 0. 723 95% CI = 0. 622-0. 825 with good calibration curves observed for both validation data sets as well as ideal curves in terms of discrimination ability. Conclusion The GLIM criteria is an effective tool for predicting the deterioration of nutritional status in tumor patients after radiotherapy. The nomogram model constructed based on the GLIM evaluation radiotherapy frequency and prealbumin levels can effectively predict the risk of nutritional deterioration in patients after radiotherapy. This provides valuable guidance and reference for medical staff in the radiotherapy department to implement proactive preventive nursing interventions.