10 quantum chemical descriptors of 21 aromatic compounds have been calculated by the semi-empirical quantum chemical method AM1. The Quantitative Structure-Biodegradability Relationships (QSBR) studies were performed by the multiple linear regression (MLR), principal component regression (PCR) and back propagation artificial neural network (BP-ANN),respectively. The root mean square error (RMSE) of the training and validation sets of the BP-ANN model are 0.1363 and 0.0244, the mean absolute percentage errors (MAPE) are 0.1638 and 0.0326,the squared correlation coefficients (R2) are 0.9853 and 0.9996, respectively. The results show that the BP-ANN model achieved a better prediction result than those of MLR and PCR. In addition,some insights into the structural factors affecting the aerobic biodegradation mechanism were discussed in detail.