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This paper investigates the future U.S. demand for streamlined space tourism by showing the missions and factors impacting traveler choices with machine learning. Space tourism is growing and is expected to become available to the masses soon. While private companies need to better understand the demand for space tourism to customize their services, transportation agencies require guidance to support fund management related to commercial space exploration. This work analyzes the three most prominent missions for streamlined space tourism (i.e., suborbital, orbital, and space tourism around the moon) and their selection determinants (i.e., price, safety, training, number of passengers, take-off locations, among other decision-maker factors). A stated preference experiment is constructed to collect data that is analyzed using machine learning. Results provide valuable insights into the mixed opinions of Americans with respect to space tourism, their mission preferences, and risk considerations. • Space tourism serves a niche of high-income travelers. • We investigate the future U.S. demand if space tourism is available to the masses. • A stated preference experiment is constructed to collect data from Americans. • The collected dataset is analyzed using machine learning paradigms. • Results unveil the mission and traveler factors impacting space tourism choices. [ABSTRACT FROM AUTHOR]