Background: Synovial sarcoma is an uncommon soft sarcoma that lacks prognostic prediction models. The nomograms were employed to predict patients’ survival of synovial sarcoma. Methods: Materials collected from 1941 synovial sarcoma cases in the SEER database were analyzed. We employed univariate and multivariate cox analyses to identify the independent prognostic variables. Based on these outcomes, the nomograms were built for predicting 1-, 3-, and 5- year overall survival rate and disease-specific survival rate and then validated in external dataset. C-indices, calibration plots and ROC curves were applied to assess nomogram accuracy. Results: Patients were randomly classified into the training (n=1361) and testing (n=580) cohorts. Age, race, sex, primary anatomic site, chemotherapy, subtypes, surgery, SEER historic stage and tumor size were identified as independent prognostic variables (P<0.05) and then the nomogram of overall survival was constructed. Similarly, the nomogram of disease-specific survival was constructed. C-indices of training cohort for predicting overall and disease-specific survival were 0.779 and 0.779, respectively. Corresponding values of testing cohort were 0.769 and 0.765, respectively. The AUC values of prognostic model in the training cohort at 1-, 3-, 5- years of overall survival were 0.845, 0.785, and 0.788, respectively. Corresponding of disease-specific survival were 0.835, 0.783, and 0.787, respectively. The calibration plots illustrated excellent consistency between the survival rate of predicted and actual survival. Conclusion: we constructed the reliable nomograms for synovial sarcoma patients to predict overall and disease-specific survival, which can offer precise and personalized survival prediction.