In order to determine current tree condition and predict future growth using LiDAR data, tree height, diameter at breast height, diameter 4 m above the ground, tree volume, tree volume growth, diameter at breast height growth and diameter growth 4 m above ground for individual trees were estimated from various crown height metrics and measurements obtained using a small footprint airborne laser scanner flown over a planted forest in Japan. Ground-truth values for tree height, diameter at breast height, diameter 4 m above ground, tree volume, and volume and diameter growth were collected. The actual values were compared with the laser-derived crown height metrics, including: percentiles, maximum, mean, coefficient of variation and crown density, all for the first and last crown height laser pulses. The regressions explained 75–79 % of the variability in ground-truth tree height, diameter at breast height, diameter 4 m above ground and tree volume. Cross-validation of the regressions revealed standard deviations of the differences between predicted and ground-truth values of 1.30 m (6.7 %), 5.2 cm (22.2 %), 3.8 cm (18.7 %) and 0.22 m3 (43.3 % of ground-truth mean), respectively. The regressions also explained 69–77 % of the variability in ground-truth averages. Cross-validation of the regressions revealed standard deviations of the differences between predicted and ground-truth values of 0.15 cm yr−1 (43.7 %), 0.1 cm yr−1 (31.0 %) and 0.008 m3 yr−1 (58.5 % of ground-truth mean), respectively. The study confirms that it may be possible to predict individual tree growth based on LiDAR data.