Following typical forest inventory protocols, individual tree volume estimates are generally derived via diameter-at-breast-height (DBH)-based allometry. Although effective, measurement of DBH is time consuming and potentially a costly element in forest inventories. The capacity of airborne light detection and ranging (LiDAR) to provide individual tree-level information poses options for estimating tree-level attributes to enhance the information content of forest inventories. LiDAR provides excellent height measurements and, given the physiologic scaling connection of plant height and volume, using individual tree height-volume relationships could overcome errors associated with the intermediate step of inferring DBH from LiDAR. In this study, 60 Abies grandis (grand fir: 6 cm–64 cm DBH) were destructively sampled to assess stem volume across the Intermountain West in order to develop individual tree height-to-stem volume relationships. Results show DBH (r2 > 0.98) and height (r2 > 0.94) are significantly (p < 0.001) related to stem volume via power relationships. LiDAR-derived heights provided a 12 % RMSE improvement in accuracy of individual tree volume over LiDAR-regressed DBH estimates. Comparing height-based estimates with an existing regional allometry by mapping stem volume in a grand fir-dominated stand yielded a 6.3 % difference in total volume. This study demonstrates LiDAR's potential to estimate individual stem volume at forest management scales, utilizing height-volume relationships.