In line with novel service models, facial recognition systems are promising in hotels, as they can optimize legacy consumer tasks (e.g., authentication, payment) and increase security. Using data collected from a nationwide sample of U.S. hotel consumers, this study empirically validated a conceptual model that explains consumers’ intentions to use facial recognition systems based on system perceptions (i.e., performance and effort expectancy), congruity with self-image, trust in hotel, and positive and negative anticipated emotions. Performance expectancy, trust in organization, and positive anticipated emotions significantly influenced intentions, while congruity with self-image and effort expectancy significantly influenced performance expectancy.