In this paper we develop a Bayesian network (BN) that relates offshore storm conditions to their accompagnying flood characteristics and damages to residential buildings, following on the trend of integrated flood impact modeling. It is based on data from hydrodynamic storm simulations, information on land use and a depth-damage curve. The approach can easily be applied to any site. We have chosen the Belgian village Zeebrugge as a case study, although we use a simplified storm climate. The BN can predict spatially varying inundation depths and building damages for specific storm scenarios and diagnose under which storm conditions and where on the site the highest impacts occur.