Since the 1970s, patient selection for cardiac stress testing—using electrocardiographic, nuclear, and echocardiographic modalities—has relied on estimating the pretest likelihood of obstructive coronary artery disease (oCAD). In recent years, several algorithms have integrated coronary artery calcium (CAC) scores into predictive models for assessing oCAD risk. However, even the simplest of these models combine CAC with other variables such as age, sex, and clinical symptoms.1