Coarse woody debris (CWD) is an essential component of forest ecosystems that provides habitat for diverse species, functions in water and nutrient cycling, and can be a potential surface fuel in wildfires. CWD detection and mapping would enhance forestry and wildlife research and management but passive remote sensing technologies cannot provide information on features beneath forest canopy, while field-based CWD inventories are not practical for mapping CWD over large areas. Airborne light detecting and ranging (LiDAR) is a remote sensing technology that provides detailed information on three-dimensional vegetation structure that could overcome limitations of passive remote sensing technologies and field-based inventories. Our objectives were to evaluate whether airborne LiDAR could be used to detect individual pieces of CWD. We measured 1679 pieces of CWD at 144 field plots from 2015 to 2016. We acquired high-density (∼24 first returns/m2) LiDAR data in 2014, filtered out canopy and sub-canopy returns using a height threshold based on field measurements of CWD, and used height-filtered data to determine which field-measured pieces of CWD were visible in the resulting point cloud. CWD pieces that were detected constituted 50% of plot CWD volume, and there was a strong, positive correlation between total plot CWD volume and volume of detected pieces (r = 0.96). Overall, we detected 23% of the individual pieces of CWD we measured. Large pieces of CWD were most likely to be detected, with the majority of pieces ≥30 cm diameter or ≥13.9 m long detected. Canopy density, shrub density, and forest type did not influence detection probability. CWD detection rates increased from 1 pulses/m2 to 16 pulses/m2, and CWD detection rate was constant from 16 pulses/m2 to 24 pulses/m2. Our results demonstrate that airborne LiDAR can be used to detect CWD. LiDAR-based detection and mapping of CWD will be most useful for applications that focus on larger and longer pieces of CWD or applications focused on total CWD volume.