The hazel grouse Bonasa bonasia is declining in many areas within its European distribution, particularly in managed forests. Adequate habitat management may thus be crucial for the regional survival of the species. So far management activities have tended to focus on the local scale. However, for the sustainable management of the hazel grouse and its habitat, the landscape scale also needs to be considered. We therefore evaluated whether habitat suitability for hazel grouse can be quickly, but adequately, modelled at the landscape scale with information obtained from aerial photographs. We mapped hazel grouse records in a forested area typical of large tracts of the Swiss Jura mountain range, and extracted data on habitat composition from infrared aerial photographs applying a bird-centred sampling approach. We then used the hazel grouse records together with an equal-sized data set of non-grouse plots to build predictive habitat suitability models using a generalised linear model (GLM) and a classification tree (TREE). The models were evaluated and then applied spatially explicitly to the 25 km² study area to compare their predictions for hazel grouse distribution. Hazel grouse preferred vertically and horizontally richly structured forest stands. Forest edge density, shrub and herb cover, stand structure and development stage were essential habitat variables. The resulting 5-fold cross-validated predictive habitat models performed well, having a kappa of 0.62 (GLM) and 0.8 (TREE), and a correct classification rate of 0.81 (GLM) and 0.90 (TREE). This suggests that predictive modelling based on a bird-centred analysis is an efficient way to assess habitat suitability for hazel grouse habitat management at the landscape scale.