〔Abstract〕 Objective To construct nomograms using data extracted from the surveillance, epidemiology, and end results(SEER) program database to predict overall survival(OS) and cancer-specific survival(CSS) for patients with choroidal melanoma(CM), and to evaluate the epidemiological characteristics, survival periods, and prognostic factors of CM patients. Methods Data on patients diagnosed with CM from 2010 to 2020 were extracted from the SEER database. The included patients were randomly divided into a training set(n=1,841) and a validation set(n=789) at a 7:3 ratio. Univariate Cox regression analysis was conducted in the training set, followed by incorporation into a multivariate Cox proportional hazards regression model. Independent influencing factors were screened in the multivariate Cox regression model to construct nomograms predicting 3-year and 5-year OS and CSS for CM. Decision curve analysis(DCA) was used to assess the clinical utility of the prediction models by quantifying the net benefit of the nomograms in decision-making support, and comparisons were made with the SEER stage model. Individual risk scores were obtained based on the established nomograms. Results A total of 2,630 patients were included in the study. The results indicated that gender, age, liver metastasis, surgery, radiotherapy, and chemotherapy were independent risk factors affecting OS in CM patients. Age, liver metastasis, surgery, and chemotherapy were independent risk factors affecting CSS in CM patients. The nomograms for 3-year and 5-year OS and CSS showed strong discriminative ability. Furthermore, in the validation set for OS and CSS, DCA indicated that the nomograms had good clinical potential. Kaplan-Meier(K-M) curves demonstrated that in both the training and validation sets, patients in the high-risk group had significantly lower OS and CSS rates compared to those in the low-risk group. Conclusion Age, liver metastasis, surgery, and chemotherapy are common predictors of OS and CSS in CM patients. A relatively comprehensive and accurate prognostic nomogram model based on the SEER database has been established. After calibration and further refinement, this nomogram model can be applied clinically to guide the treatment and prognosis of patients.