Objective: To identify, among different Cardiovascular Risk Predictors (CVRP), which have the best associations with Coronary Artery Calcification (CAC). Methodology: Cross-sectional study, with dyslipidemic (age >18), to investigate the association between CVRP [anthropometrics, biochemicals, clinicals, Ankle-Brachial Index (ABI), arterial stiffness] and Coronary Calcium Score (CCS), which was classified according to (1) CCS=0, CCS=1-100, CCS>100, (2) CCS=0, CCS=1-99, CCS=100-299, CCS>300 and (3) dichotomous (CCS=0 or CCS>P75/CCS>100). Bivariate descriptive and inferential statistics were performed. ROC curves estimated the CAC risk of the independent variable. The univariate logistic regression model identified the probability of CAC and established the sensitivity and the specificity of each predictor and the multivariate identified higher risk variables and their respective Odds Ratio (OR). Results: 180 patients evaluated, 65.5% were women, mean age 59.8. CAC was associated with Waist Circumference (p=0.03), A Body Shape Index Risk-ABSIR (p<0.001), Conicity Index (p<0.001), Waist-to-Height Ratio (p<0.001) (T Student test); Pulse Wave Velocity-PWV was associated with CAC for both (1) and (2) CCS classification (p<0.001) (Anova test with Duncan post-hoc test) and it also showed greater sensitivity on ROC curve (3) (AUC 0.61, with a sensitivity of 72.2). In multi-adjusted regression, ABSIR increased the risk of CAC by 3.5 times (CI 95%=1.38-1.64, p=0.001) and PWV by 36% (CI 95%=1.13-1.64, p<0.01). Conclusions: ABSIR and arterial stiffness (PWV) made it possible to obtain a better value for CAC prognosis, being the ABSIR an easy and cheap method, very useful in Public Health.