With growing city tourism, there is an increasing need for urban travel demand models to consider traffic generated by visitors. Existing research has concentrated on socio-demographic and journey-related factors to determine what influences the mode choice of tourists. In contrast, revealed preference data, like travel time, is almost never considered. In this article, we present the results of discrete choice modeling of city tourists’ mode choice based on revealed preference data from a survey we conducted in Kassel, Germany. We used multinomial logit models and determined the model parameters using maximum likelihood estimations. Surprisingly, travel time played a smaller role in mode choice than understood from previously established knowledge about everyday mobility. In the final model, travel time was only significant for the alternative walking. Also, most other sociodemographic and journey-related variables showed no significant influence. The final model reproduced the mode choice, but the goodness of fit was lower than expected from other research. We conclude that modeling the travel behavior of tourists is more complex than everyday mobility. An alternative approach that we suggest would be to model trip chains rather than single trips.