Bicuspid aortic valve (BAV) disease is the most common congenital heart defect worldwide. When severe, symptomatic aortic stenosis ensues, the treatment has increasingly become transcatheter aortic valve replacement (TAVR). The purpose of this review is to identify BAV classification and imaging methods, outline TAVR outcomes in BAV anatomy, and discuss how computational modeling can enhance TAVR treatment in BAV patients. TAVR use in BAV patients, when compared to use in tricuspid aortic valves, showed lower device success rate, and there remains no long-term randomized trial data. It has been reported that BAV patients with severe calcification increase the rate of complications. Additionally, the asymmetrical morphology of BAVs often results in asymmetric stent geometries which have implications for increased thrombosis risk and decreased durability. These adverse outcomes are currently very difficult to predict from routine pre-procedural imaging alone. Recently developed patient specific experimental and computational techniques have the potential to assist in filling knowledge gaps in the mechanisms of these complications and provide more information during preclinical planning for better TAVR selection in low surgical risk BAV patients. Efficacy of TAVR for irregular BAV anatomies remains concerning due to the lack of a long-term randomized trial data, their increased rate of short-term complications, and signs that long-term durability could be an issue. More knowledge on identifying which BAV anatomies are at greater risk for these adverse outcomes can potentially improve patient selection for TAVR versus SAVR in low surgical risk BAV patients.