Objective To develop a risk prediction model for venous thromboembolism (VTE) in lung cancer patients receiving immune checkpoint inhibitors (ICIs). Methods A retrospective analysis was conducted on lung cancer patients treated with ICIs at West China Hospital of Sichuan University between January 2018 and March 2022. The primary outcome was newly diagnosed VTE within 12 months. Independent risk factors for VTE were identified using multivariable logistic regression analysis in the training cohort and used to construct a risk prediction model, which was subsequently validated in a validation cohort. The performance of the model was evaluated using receiver operating characteristic (ROC) curve. Results During the 12-month follow-up period, a total of 105 patients developed VTE, with an incidence rate of 9.4% (105/1115). Multivariable logistic regression analysis identified an Eastern Cooperative Oncology Group performance status (ECOG PS) ≥2, severe pulmonary disease, respiratory failure, abnormal pulmonary function, a history of VTE, prior chemotherapy, and corticosteroid therapy as independent predictors of VTE. The area under the ROC curve (AUC) of the prediction model was 0.822 (95%CI 0.762-0.882) in the training cohort and 0.779 (95%CI 0.687-0.871) in the validation cohort. Based on the model score, the patients were stratified into three risk categories for VTE: low risk (0-1 points), intermediate risk (2-3 points), and high risk (≥4 points). Conclusion The VTE risk prediction model developed in this study demonstrated good predictive performance in lung cancer patients receiving ICIs, and may serve as a practical tool for guiding individualized thromboprophylaxis strategies in clinical practice.