The disasters in seabuchkthorn shrubberies, Hippophae rhamnoidea in China, can be divided into two kinds, i.e., biotic and abiotic disasters. The biotic disasters are mainly caused by seabuckthorn carpenterworms——Holcocerus hippophaecolus, which have been a severe boring pest of seabuckthorn in Inner Mongolia Autonomous Region, Liaoning, Shanxi, Ningxia and Shanxi Provinces in recent years. The abiotic disasters include bad site condition and unsuitable meteorological condition. These disasters result in the decline of growing vigor and death eventually in large scale in wide areas in Northern China. An investigation on health status of seabuchkthorn shrubberies was made in Jianping County, Liaoning Province, and Aohan County, Inner Mongolia. Totally fifty sampling plots were surveyed. The field survey includes mortality of seabuckthorn, percentage of crown with leaves, damage rate by the pest, population density of larvae in rootstocks ranging from ground to 20cm underground, average height, bottom diameter of seabuckthorn, direction of slope, position of slope, grades of slope. Based on Fuzzy evaluation, weights of four damage indexes which include mortality of seabuckthorn, percentage of crown with leaves, damage rate by the pest, population density were reset. The degrees of damaged Seabuckthorn shrubberies are measured by healthy, light, medium, severe according to Fuzzy evaluation. With direction of slope, position of slope, grades of slope, height, bottom diameter and population density as predictive factors, developed were BP neural network for classifying and predicting the damage degree of Seabuckthorn shrubberies and Logistic model. The results of prediction show that the qualified rates of fitting and prediction using BP model amount to 88.1% and 75% respectively. The rate of concordant in Logistic model is 69.4 %. The prediction of BP model agrees with that of Logistic model. Ceteris paribus，the effects on damage degree arising from position of slope is 4.93 times of that arising from other factors.