In order to study the spectroscopic characters of explosives in the terahertz region and realize the identification of explosives, the terahertz absorption spectra of explosives have been measured by using terahertz time-domain spectroscopy (THz-TDS) system. These samples which include pure explosives RDX, HMX,DNT,PETN, TNPG and mixed explosives 8701,PW0,R791,R852,SU-1,8702 were then identified by two types of artificial neural networks(ANNs)—self-organized mapping(SOM)and muti-layer perceptron(MLP)—through repetitive modeling and adequate training. High positive identification rate (above 95%) and low false alarm rates have been gained. The results indicate that it is feasible to apply these two ANNs on the identification of different types of explosives, and it also provides an effective method in the inspection and identification for explosives using THz-TDS.