Objective To develop and validate a prediction model for the 5-year survival rate of patients with advanced non-small cell lung cancer (NSCLC) by integrating the basic information and clinical data of patients.Methods A total of 313 patients with advanced NSCLC from the Cancer Hospital of Shanxi Medical University were randomly assigned (7∶3) to a training cohort and an internal validation cohort. Univariate and multivariate Cox regression analyses were performed to screen out the independent factors that affect the 5-year survival rate of patients and create a prediction model. The performance of the model 0020 was evaluated using the consistency index (C-index), calibration curve, and receiver operating characteristic (ROC) curve. The clinical decision curve analysis (DCA) was used to assess the clinical benefit of the prediction model. A nomogram was also created to visualize the predicted probability of 5-year survival.Results A good prognostic model was developed and a nomogram for model visualization was plotted. The nomogram was constructed with nine variables: age, smoking history, N stage, bone metastasis, platelet count, lymphocyte count, lactate dehydrogenase, Ki67, and first-line treatment regimen. Based on the median risk score of the training cohort, all individuals were divided into high-risk group and low-risk group, and the high-risk group had poor overall survival (OS) in both cohorts (P<0.05).Conclusion A clinical prediction model was established to predict the 5-year survival rate of patients with advanced NSCLC.