Estimating biodiversity in complex habitats, particularly in forests, is still a major challenge for ecologists and conservationists. In ground-breaking work, Robert MacArthur and his colleagues quantified relationships between bird and vertical vegetation diversity, and found that the diversity of vegetation structure strongly influenced bird species diversity. However, they were limited in spatial extent when describing vertical vegetation structure due to the labor-intensive nature of data collection. Current remote sensing techniques, such as LiDAR, can describe ecologically relevant measurements of forest structure across broad extents, and thus, there are increasing efforts to examine relationships between LiDAR-derived data and patterns of animal biodiversity. LiDAR-based data have been utilized for silvicultural assessments for over a decade, but LiDAR use in biodiversity studies is more recent. LiDAR data can assist in the assessment of local animal diversity across taxa, and might assist in larger scale biodiversity assessments in remote and rugged environments. In the following chapter, we first briefly discuss the role of vegetation structure in biodiversity studies, followed by a description of the variables that are most commonly used in biodiversity studies. We then give an overview of biodiversity studies that have utilized LiDAR in forests to date. Although there is a growing body of literature relating LiDAR-derived variables to single species distributions and habitat quality, we focus this chapter solely on studies that address animal species diversity in forested landscapes. We conclude with a discussion of future directions concerning biodiversity assessments in forested systems that might benefit from the use of LiDAR-based data.