In transportation architecture, wayfinding quality is a crucial factor for determining transfer efficiency and level of service. When developing architectural design concepts, designers often employ their visual attention to imagine where passengers will look. A saliency model is a software program that can predict human visual attention. This research examined whether a saliency model or designer visual attention is a good predictor of passenger visual attention during wayfinding inside transportation architecture. Using a remote eye-tracking system, the eye-movements of 29 participants watching 100 still images depicting different indoor scenes of transportation architecture were recorded and transformed into saliency maps to illustrate participants’ visual attention. Participants were categorized as either “designers” or “laypeople” based on their architectural design expertise. Similarities were compared among the “designers’” visual attention, saliency model predictions, and “laypeople’s” visual attention. The results showed that while the “designers’” visual attention was the best predictor of that of “laypeople”, followed by saliency models, a single designer’s visual attention was not a good predictor. The divergence in visual attention highlights the limitation of designers in predicting passenger wayfinding behavior and implies that integrating a saliency model in practice can be beneficial for wayfinding design.