LiDAR remote sensing allows the direct retrieval of vegetation structure parameters and has been widely used to assess habitat quality for various species. The aim of this study is to test whether LiDAR can help in providing estimates of habitat suitability over larger scales and inform conservation management planning in stronghold areas of an endangered forest mammal, the red squirrel (Sciurus vulgaris L.). The Eurasian red squirrel is endangered in the UK and under strict legal protection. Hence, long-term habitat management is a key goal of the UK conservation strategy. This involves understanding habitat preferences of the species. In a previous study, we demonstrated the importance of forest structure for red squirrels’ habitat preference. We used a general linear model (GLM) to relate the distribution and abundance of squirrel feeding signs to mean canopy closure, mean tree height, and the total number of trees at the plot level. However, this analysis was limited to a few sample areas. In the current study, we implement the GLM using LiDAR-derived explanatory variables in Abernethy Forest. Results suggest that when forest structure is considered, only 27% of the total forest area is highly suitable for red squirrel. Implications for management are discussed.