Credible forecasts of long-distance travel are an important tool for evaluating proposed intercity transportation improvements, including intercity highway and transit projects. Although researchers have studied the topic and have developed frameworks for modeling long-distance travel behavior, these research models have not been integrated into comprehensive model systems used for a wide range of applications. This paper presents a long-distance travel model that bridges the gap between research and practice. It is based on a rigorous behavioral framework that models the unique aspects of long-distance travel, such as a less regular frequency of trips and a different set of modal alternatives. The model structure includes the choice of whether to travel, the selection of the days on which to travel, scheduling to a specific time of day, destination choice, and mode choice. The model is sensitive to important descriptive variables, including the demographic characteristics of travelers, the attractiveness of possible destinations, and the levels of service of air, transit, and highway networks. It has been successfully implemented as part of the Ohio statewide model, which also features an advanced tour-based model of short-distance travel. Through this integration, it allows for behavioral consistency within the entire model system and competition among all travelers for transportation capacity. Lessons are learned about the data needs and research needs to further improve long-distance travel models.