Introduction: The risk of venous thromboembolism (VTE) varies among tumour types, and different cancer type-specific risks for VTE prediction remain undefined. We aimed to establish a prediction model for non-small lung cancer (NSCLC)-associated VTE. Materials and methods: We analysed data from a prospective cohort of patients with newly diagnosed NSCLC. We then developed a VTE risk prediction model using data of patients who were recruited from 2013 to 2017 (n = 602, development cohort) and validated this model using date of patients recruited from 2018 to 2019 (n = 412, validation cohort). The cumulative 6 months VTE incidence observed in both cohorts was calculated. Results: The parameters in this new model included Eastern Cooperative Oncology Group (ECOG) performance status >2 (1 point), EGFR mutation (-1 point), neutrophil count >= 7.5 x 10(9)/L (2 points), hemoglobin <115 g/L (1 point), CEA >= 5.0 ng/mL (2 points), and D-dimer level >= 1400 ng/mL (4 points). The cross-validated concordance indices of the model in the development and validation cohorts were 0.779 and 0.853, respectively. Furthermore, the areas under the curve in the two cohorts were 0.7563 (95% confidence interval [CI]: 0.6856-0.8129, P < 0.001) and 0.8211 (95% CI: 0.7451-0.8765, P < 0.001) for development and validation cohorts, respectively. Conclusions: The new VTE risk prediction model incorporated patient characteristics, laboratory values, and oncogenic status, and was able to stratify patients at high risk of VTE in newly diagnosed NSCLC within 6 months of diagnosis.