This paper proposes a method for identifying organic compounds by applying a differential principal-component-analysis (PCA)-support-vector-machine (SVM) to the terahertz time-domain spectral data. First, the terahertz absorption spectrum is calculated according to the terahertz time-domain signal of the material sample; then, the features of the data in the frequency range of 0.2-2.5 THz are extracted. During the feature extraction, an expansion-of-sample-size method based on differential data is proposed and combined with the PCA method to achieve the feature extraction. Finally, the SVM is used to establish a mathematical model for the corresponding relationship between the extracted features and the material category, and the unknown samples are identified according to this model. The terahertz-spectral data of 15 organic compounds are identified using the proposed method, and the correct recognition rate is 93.33%. The experimental results show that the correct recognition rate of organic compounds by the proposed method is the highest when compared with those by the linear-discriminant analysis method and the absorption peak frequency-amplitude method.