Airport development is a critical factor for regional growth, improving connectivity, and stimulating economic growth. Considering the complexity of planning and policy making in this area, multiple models and frameworks have been introduced to support decision-making processes. Among these, Discrete Choice Models (DCM) stand out for their capacity to project market flows, assess the validity and benefits of implementing airport modifications, tailor policies, improve the operations' service level, and boost revenues. Given their extensive use and importance, a thorough review of DCM applications within the context of air transportation is both timely and necessary. This review organizes and evaluates the use of DCMs in air transport research. Both descriptive and predictive applications of DCMs are analyzed, focusing on choices related to airports and related levels, such as access mode and airline decisions. Each reviewed study is classified based on the type of model used, application context, data characteristics, employed variables, and methodological contributions. Through this analysis, six prevailing gaps are identified in the current state of DCM application in air transportation: improve data quality, enhance models with detailed trip and passenger information, explore advanced modeling techniques, incorporate general correlation and substitution structures, consider non-compensatory decision-making processes, and extend applications to new geographic and temporal contexts.