Metabolic syndrome (MS) is widely believed to be an important risk factor for cardiovascular disease (CVD). We assessed whether a model based on MS improved prediction of CVD and total mortality over the Framingham's general CVD system (FRS) and whether MS was better than its individual components. Prospective cohort study of 855 participants randomly selected from the general population. Cox proportional hazards models were used to estimate the hazard ratios selecting a composite endpoint of CVD and total mortality. The performance of the FRS was compared with that of 4 MS-based models that differed in their use of individual components of MS as well as in the use of optimized cut-points of MS. The assessment included metrics of discrimination, calibration, and risk reclassification. Of all the models, only the model containing the 5 optimized components of MS improved model fit (deviance 10.7, P = 0.005), discrimination (difference of areas under the receiving operating curves 0.018), and risk reclassification in participants without events (net reclassification index 5.97, P = 0.01). The addition of optimized waist circumference to the FRS model improved the performance more than any other MS-based model. Every model containing the dichotomous definition of MS failed to improve model fit, discrimination, and risk reclassification. MS did not contribute predictive information over the FRS for the 5-year risk of CVD and total mortality. Some individual components of MS, in particular waist circumference, might play a role as part of the FRS provided their cut-off points are optimized.