Multi-trophic diversity is often overlooked in land management decisions due to the absence of cost- and time-effective assessment methods. Here, we introduce a new method to calculate a combined terrain and canopy structural complexity metric using LiDAR data, enabling the prediction of multi-trophic diversity-a combined diversity metric that integrates diversity across trophic levels. We selected 34 forested sites of the National Ecological Observatory Network to test the model by using observed data on plant presence, beetle pitfall trap, and bird count to calculate multi-trophic diversity. Our results show that multi-trophic diversity increases with increasing structural complexity, but this relationship differs across different forest types. The environmental and geographic factors account for about 40% variability in multi-trophic diversity, which further increases to about 60% when combined with structural complexity. This research offers a powerful approach to evaluate biodiversity at a landscape scale using remotely sensed data and highlights the importance of considering multi-trophic diversity in land management decisions.