BACKGROUND: Coronary obstruction (CO) during transcatheter aortic valve replacement (TAVR) is rare but potentially fatal. Computed tomography (CT)-based risk assessment algorithms aim to identify high-risk patients, but their utility remains underexplored. OBJECTIVES: The aim of this study was to examine the clinical utility of a CT-derived algorithm for predicting CO during TAVR and identify predictors of CO despite coronary protection (CP). METHODS: In this prospective study, 164 patients at risk for CO during TAVR were enrolled. Preprocedural CT was used to classify risk using a published algorithm. A novel volumetric parameter, valve-to-coronary volume (VTCV), was calculated in high-risk cases using sinus width and valve-to-coronary (VTC) distance. The decision to use CP was left to the heart team. Clinical endpoints followed Valve Academic Research Consortium 3 definitions. RESULTS: According to the CT-based algorithm, 58.5% of patients (96 of 164) were at low risk, 24.4% (40 of 164) at intermediate risk, and 17.1% (28 of 164) at high risk. CP was performed in 12.8% of low-risk patients (16 of 125), 52.8% of intermediate-risk patients (28 of 53), and 93.9% of high-risk patients (31 of 33). All CO events (n = 7) occurred in the high-risk group. VTC distance and VTCV were significantly lower in patients with CO (P = 0.006 and P = 0.005, respectively). VTCV independently predicted CO (area under the curve, 0.841; 95% CI: 0.702-0.979; P < 0.001), outperforming VTC distance alone. The predictive value of VTCV was validated in an external cohort including 11 European centers. CONCLUSIONS: A CT-based algorithm stratifies patients into 3 CO risk categories, though the decision for CP in clinical practice seems to incorporate additional clinical and procedural variables. Although CP reduces CO risk, its efficacy is limited in patients with very small VTCV, which can be predicted preprocedurally via CT. (Leipzig TAVR Registry; NCT05015452).