Publication Abstract Species distribution models (SDMs) are useful tools for identifying the distribution of marine species in data limited environments. Outputs from SDMs have been used to identify areas for spatial management, analyzing trawl closures, quantitatively measuring the risk of bottom trawling, and evaluating protected areas for improving conservation management. Cold-water corals are globally distributed habitat forming organisms that are vulnerable to anthropogenic impacts and climate change, but data deficiency remains an ongoing issue for the effective spatial management of these important ecosystem engineers. In this study, we constructed 11 environmental seabed variables at 500m resolution based on the latest multi-depth global datasets and high-resolution bathymetry. Ensemble modeling methods were used to predict the global habitat suitability for ten widespread cold-water coral species, including six reef Scleractinian framework-forming species and four large gorgonian species. Temperature, depth, salinity, terrain ruggedness index, carbonate saturation state and chlorophyll were the most important factors in determining the global distributions of these species. The Scleractinian species Madrepora oculata showed the widest niche breadth, whilst most other species demonstrated somewhat limited niche breadth. The shallowest study species, Oculina varicosa, had the most distinctive niche of the group. The model outputs from this study represent the highest resolution global predictions for these species to date and are valuable in aiding the management, conservation and continued research into cold-water coral species. Data description These datasets (compressed Zip archives) contain the ten global environmental layers that were generated for the publication Tong et al., (2023) doi: 10.3389/fmars.2023.1217851, using a trilinear interpolation approach based on the 500m GEBCO bathymetric data product. These layers are representations of seafloor conditions. Please refer to the manuscript for methodological details. These files are provided in an ArcGIS compatible TIFF format that is readable by various GIS packages and can be imported to R. aoxu.zip = Apparrent Oxygen Utilization diso2.zip = Dissolved Oxygen nit.zip = Nitrate oa.zip = Omega Aragonite oc.zip = Omega Calcite ph.zip = pH phos.zip = Phosphate sal.zip = Salinity sil.zip = Silicate temp.zip = Temperature