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The current cardiovascular risk tables are based on a 10-year period and therefore, do not allow for predictions in the short or medium term. Thus, we are unable to take more aggressive therapeutic decisions when this risk is very high.To develop and validate a predictive model of cardiovascular disease (CVD), to enable calculation of risk in the short, medium and long term in the general population.Cohort study with 14 years of follow-up (1992–2006) was obtained through random sampling of 342,667 inhabitants in a Spanish region.Main outcome: time-to-CVD. The sample was randomly divided into 2 parts [823 (80%), construction; 227 (20%), validation]. A stepwise Cox model was constructed to determine which variables at baseline (age, sex, blood pressure, etc) were associated with CVD. The model was adapted to a points system and risk groups based on epidemiological criteria (sensitivity and specificity) were established. The risk associated with each score was calculated every 2 years up to a maximum of 14. The estimated model was validated by calculating the C-statistic and comparison between observed and expected events.In the construction sample, 76 patients experienced a CVD during the follow-up (82 cases per 10,000 person-years). Factors in the model included sex, diabetes, left ventricular hypertrophy, occupational physical activity, age, systolic blood pressure × heart rate, number of cigarettes, and total cholesterol. Validation yielded a C-statistic of 0.886 and the comparison between expected and observed events was not significant (P: 0.49–0.75).We constructed and validated a scoring system able to determine, with a very high discriminating power, which patients will develop a CVD in the short, medium, and long term (maximum 14 years). Validation studies are needed for the model constructed.