In order to determinate the content of styrene butadiene styrene block copolymer(SBS) in SBS modified asphalt accurately, the Fourier transform infrared spectroscopy(FTIR) spectra of modified asphalts containing different SBS contents were collected by using FTIR instrument, and the determination model for SBS content in modified asphalt was established based on deep neural network(DNN）. The influences of different factors on the accuracy of the determination model were studied, and the accuracy, susceptibility and applicability of the model were evaluated. The results show that mean square error of the SBS content determination model is reduced by 70% by dimension reduction and noise reduction. Determination accuracy for SBS content in modified asphalt using DNN method compares favourably with that using standard curve method and random forest method. It also has good sensitivity and applicability to determination of SBS content in modified asphalt by the DNN determination model.