In this paper, the combined terahertz time-domain spectroscopy (THz-TDS) and chemometrics method is proposed to identify four different parts of Panax notoginseng rapidly and nondestructively. The research objects of the taproot, scissor, rib, and hairy root of P. notoginseng are taken. The refractive index, absorption coefficient, time-domain, and frequency-domain spectra of the samples are analyzed. It is found that the terahertz spectra of different parts of P. notoginseng are significantly different, so the absorption coefficient of samples is selected to establish models. Firstly, the baseline correction, multiple scattering correction, and normalization algorithms are used to preprocess the absorption coefficient in 0.5–2.0 THz to remove noise. Then, the Kennard–Stone (KS) algorithm is used to divide the model set and the prediction set at the ratio of 3:1, and the successive projection algorithm (SPA) is used to select the characteristic frequency points of the samples. Finally, the chosen characteristic variables are input into the support vector machine (SVM) and linear discriminant analysis (LDA) algorithm to establish the qualitative analysis models, respectively. In the SPA-SVM models, the performance of the SPA-SVM model under the linear kernel function by baseline is best, the accuracy of the training set of it is 99.50%, and the accuracy of the test set of it is 99.25%. In the SPA-LDA models, the performance of the SPA-LDA model by baseline is best, and the accuracy of the training set of it is 100%, and the accuracy of the test set of it is 100%. And the value of cumulative variance contribution is proposed to assess whether the variable is good or bad to model. The results show that the combined THz-TDS and chemometrics method can be used to realize rapid, accurate, and nondestructive identification of different parts of P. notoginseng.