Different multimorbidity patterns can influence health outcomes. We investigated their association with the risk of cardiovascular events in CUORE (baseline 2008–2012), an Italian cohort of randomly selected individuals from general population aged 35–69 years. Latent Class Analysis was used to identify homogeneous groups of multimorbid individuals (≥2 diseases) with similar underlying disease patterns. Cardiovascular disease (CVD) risk scores were estimated for each pattern, separately for men and women, and the one-way Anova test was used to evaluate significant differences between classes. Final sample consisted of 6,614 individuals (50% male, mean age 52 [SD 9.9]). Four multimorbidity patterns were identified and named after their overexpressed diseases: unspecific; inflammatory and metabolic; respiratory, cancer and anemia; obesity. We observed significant differences in cardiovascular risk scores between patterns, both in males and females; the unspecific and obesity patterns showed the highest mean cardiovascular risk scores. Multimorbidity patterns are differentially associated with CVD risk and their identification may provide prognostic information to improve prevention strategies.