Objective: To analyze the prognostic factors of patients with malignant solitary pulmonary nodules (SPN) and to construct a nomographic model based on CT imaging and clinical features. Methods: Sixty patients diagnosed as malignant SPN by imaging were enrolled in the study from July 2022 to June 2024 in Anyuan County People"s Hospital of Ganzhou City, Jiangxi Province. After at least 6 months of follow-up, the patients were divided into good prognosis group and poor prognosis group according to recurrence, deterioration and survival. Clinical data of the two groups were compared. The correlation factors influencing the prognosis of malignant SPN patients were screened out by univariate analysis, and then verified by multivariate Logistic analysis. Based on the screened independent risk factors, a nomogram prediction model for poor prognosis of malignant SPN patients was constructed. Receiver operating characteristic curves were used to evaluate the accuracy of the model in predicting poor prognosis in patients with malignant SPN and calibration curves were made to evaluate its consistency. Results: Among 60 patients, 15 patients had poor prognosis, the incidence was 25.00%. Logistic analysis showed that age, vascular convergence, pleural depression, lobulation, spiculation and maximum diameter of nodules were independent risk factors for poor prognosis of malignant SPN patients, and the area under the curve of nomogram model for predicting poor prognosis of malignant SPN patients was 0.769. The Hosmer-Lemeshow goodness-of-fit test confirmed that the calibration of the model was ideal (χ2=8.340, P =0.214). The calibration curve analysis further showed that the prediction probability of the model was consistent with the actual outcome, and the mean absolute error was 0.031. Conclusion: A predictive model for poor prognosis in patients with malignant SPN was established based on age, spiculation, lobulation, pleural indentation and vascular convergence. The predictive power and discriminant validity of the model were good.