<p>Malignant meningiomas are a rare type of central nervous system tumor. Therefore, little is known about the best methods for treating malignant meningiomas and their prognostic factors. The aim of this study was to identify risk factors and develop a prognostic model for patients with malignant meningiomas. First, 2360 cases of malignant meningiomas from the Surveillance, Epidemiology, and End Results database were randomly divided into the primary and validation cohorts. Next, multivariate Cox regression identified several independent predictors of survival in malignant meningioma patients. These included patient demographics (age, gender, race), tumor features (laterality, size, stage), treatment timing (months from diagnosis to treatment), treatment modality, and tumor history (counts of both in situ/malignant and benign/borderline tumors), as well as year of diagnosis. Third, a nomogram was used to represent the prediction model, which was built based on independent predictors and optimized using the Akaike information criterion. Finally, we evaluated the predictive performance using the concordance index and receiver operating characteristic curve and clinical value using decision curve analysis. Notably, the strong discrimination ability of the model was demonstrated by the concordance index of the nomogram and the area under the receiver operating characteristic curve, both of which were between 0.7 and 0.8. The calibration plots in both cohorts showed high agreement between actual observation and nomogram prediction, and decision curve analysis demonstrated the significant clinical value of the nomogram. In conclusion, the nomogram is a practical and useful tool for assessing prognosis and determining effective treatment approaches.</p>