To integrate the health assessment results of individual trees into the health assessment of subcompartment (or stand) scale could improve the accuracy of subcompartment (or stand) scale health assessment, and realize the coupling process between the individual tree scale and the subcompartment (or stand) scale, providing a theoretical basis for the realization of forest health management. Taking the natural Larix gmelinii forest in Great Xing' an Mountains as the object, a health assessment indicators system of individual trees was established, which included root state, canopy defoliation degree, crown transparency, crown overlap, crown dieback ratio, live crown ratio, crown skewness, and vertical competition index. The principal component analysis (PCA) was employed to eliminate the correlations, the entropy value method was adopted to confirm the weight of each indicator, and the health status of individual L. gmelinii was assessed by fuzzy synthetic evaluation (FSE) method. Based on the health assessment results, a prediction model of the individual tree health was established by discriminant analysis (DA) method. The results showed that the trees in sub-healthy gradation were up to 36.7%, and those in healthy gradation only reached 12.9%. The proportion of the trees in unhealthy gradation exceeded that of the trees in healthy gradation, occupying 21.1% of the total. The prediction accuracy of the established model was 86.3%. More rational and effective management measures should be taken to improve the tree health grade.