Coronary artery disease (CAD) is associated with significant morbidity and mortality. Coronary artery calcification (CAC) indicates presence of CAD. Absence of CAC is associated with very low risk of having CAD but not equal to zero. In this study, we aim at developing a clinical prediction tool to predict presence of obstructive CAD among patients with zero calcium score. We developed two models. A full prespecified model with 7 variables based on input from clinical experts, and a reduced model with 4 variables based on univariate screening. Both models showed an acceptable performance (c-statistics of 0.68 for both). Both models performed well when validated, externally for the full model and internally for the reduced one. We derived a clinical risk score of 20 points from the full model. We found that a score threshold of ≥ 14 is associated with presence of obstructive CAD with positive likelihood ratio of 5.5.