In order to accurately reconstruct the 3-D chlorophyll distribution of adaxial and abaxial leaves, the leaves and plants of epipremnum aureum in different growth states were selected as the experimental samples, whose spatial-spectral point cloud data were acquired by hyperspectral light detection and ranging (LiDAR), and a reconstruction method based on classification and prediction was designed. Chlorophyll content prediction models of adaxial and abaxial leaves were constructed by the partial least squares regression modeling method, to calculate the chlorophyll of different leaves, adaxial and abaxial leaves were classified with the spectral adaptive threshold selection method, and then the plant 3-D distribution of chlorophyll was reconstructed. The results show that this reconstruction method can obtain the predicted value with a coefficient of determination 0.69 and a root mean square error 4.97, which is closer to the true value. This result will provide a basis and theoretical approach for plant phenotypes research.