Citizen science (CS) and remote sensing (RS) approaches have become more reliable, thus providing higher resolution and generating a large amount of environmental data. When considering urban environments, where fragmented and highly diverse landscapes are predominant, the combination of citizen science data and remote sensing techniques with species distribution models (SDM) can play a vital role in comprehensively investigating and evaluating urban biodiversity. However, citizen science derived species distribution models for multiple avian species in dense and fragmented urban areas are rarely used. The study aims (I) to elaborate, whether CS driven SDMs can be effectively used in spatially complex urban environments; (II) to identify biodiversity hotspots and prioritize areas for nature conservation and (III) to examine, if existing protective areas correspond to species’ hotspots. Therefore, Citizen science-based datasets of 26 breeding bird species over three years were obtained for this analysis in Germany’s Ruhr Metropolis. Quality assurance, data thinning, and pseudo-absence simulations were performed. Spatial data from the ecosystem LiDAR project GEDI (Global Ecosystem Dynamics Investigation), climate data from the German Weather Service, and land use information from Copernicus were used as environmental predictors. Eleven different species distri-bution models (SDMs) were trained on species subselection by using Biomod2 for preliminary analysis. Overall model performance was evaluated via several metrics, including TSS (true skill statistics) and ROC (receiver operating characteristic). Finally, four species distribution models were used for ensemble modelling. Subsequently, a species richness analysis was performed with the aim of identifying spots with high avian biodiversity. Overall, the CS-derived SDMs performed well, with high predictive power for all of the investigated species. Within the Ruhr Metropolis, approximately 6% (250 km²) of the terrain was identified as being highly suitable for avian diversity, inhabiting at least 17 out of 26 species. Predominantly within the core urban areas, high species richness was predicted on preserved brownfields and revitalized mine sites, as well as in the remnants of formerly demarcated regional greenbelts. Additionally, regions outside of the core area, which are part of the overarching biotope network framework, proved to have high species richness capabilities for avian biodiversity. These findings aid in optimizing urban development concepts and (sub)urban green space management with respect to urban biodiversity conservation. Following the implications of the recently established Regional Biodiversity Strategy in the Ruhr Metropolis, this analysis demonstrates the importance of networked green spaces, their preservation and the need to close existing network gaps within the Ruhr Metropolis.