Effective species conservation and management requires information on species distribution patterns, which is challenging for highly mobile and cryptic species that may be subject to multiple anthropogenic stressors across international boundaries. Understanding species– habitat relationships can improve the assessment of trends and distribution by explicitly allowing high- resolution data on habitats to inform abundance estimation and the identification of protected areas. In this study, we aggregated an unprecedented set of survey data of a marine top predator, the harbor porpoise (Phocoena phocoena), collected in the UK (SCANS II, Dogger Bank), Belgium, the Netherlands, Germany, and Denmark, to develop seasonal habitat- based density models for the central and southern North Sea. Visual survey data were collected over 9 yr (2005–2013) by means of dedicated line- transect surveys, taking into account the proportion of missed sightings. Generalized additive models of porpoise density were fitted to 156,630 km of on- effort survey data with 14,356 sightings of porpoise groups. Selected predictors included static and dynamic variables, such as depth, distance to shore and to sandeel (Ammodytes spp.) grounds, sea surface temperature (SST), proxies for fronts, and day length. Day length and the spatial distribution of daily SST proved to be good proxies for “season,” allowing predictions in both space and time. The density models captured seasonal distribution shifts of porpoises across international boundaries. By combining the large- scale international SCANS II survey with the more frequent, small- scale national surveys, it has been possible to provide seasonal maps that will be used to assist the EU Habitats and Marine Strategy Framework Directives in effectively assessing the conservation status of harbor porpoises. Moreover, our results can facilitate the identification of regions where human activities and disturbances are likely to impact the population and are especially relevant for marine spatial planning, which requires accurate fine- scale maps of species distribution to assess risks of increasing human activities at sea.