This paper proposes a method to classify and recognize redwood using Terahertz time-domain spectroscopy (THz-TDS). Redwood is expensive and difficult to identify which leads to a shoddy market. The phenomenon disrupts the market order and causes huge economic losses to producers and consumers. The traditional methods of identifying redwood are difficult to give consideration to both accuracy and rapidity, therefore it is necessary to put forward a new method to supplement the traditional classification methods. Compared with the traditional methods, terahertz wave has good penetrability and fingerprint characteristics for redwood, and has great application potential in classification and identification of redwood. In this paper, five kinds of redwood (Dalbergia bariensis, Dalbergia oliveri, Bois de rose, Pterocarpus santalinus, Dalbergia cochinchinensis) are selected as test samples. The THz-TDS system is used to obtain the terahertz time-domain spectrum of wood; the terahertz frequency domain spectrum is obtained by fast Fourier transform of the terahertz time-domain spectrum of five woods, the optical parameters of the terahertz time-domain spectrum are extracted. The results show that different types of wood have time delay line and amplitude difference in time domain spectrum, the attenuation trend and amplitude are different in frequency domain spectrum, the bands of various types of redwood absorption peaks appear differently in the absorption coefficient spectrum, which all can show the differences between various types of wood, indicating that THz-TDS has feasibility for classification of redwood. The successive projections algorithm (SPA) is used to extract the characteristic frequency of the absorption coefficient spectrum and the refractive index spectrum. 28 characteristic frequency points are selected from the 260 frequency points of the absorption coefficient spectrum and the frequency band accounts for 1077%; 12 characteristic frequency points are selected from 260 frequencies of the refractive index spectrum, and the frequency band accounts for 462%. A random forest classification model and a support vector classification model based on the absorption coefficient spectrum and the refractive index spectrum are established and compared. The results show that THz-TDS has great quality to recognize wood. A random forest classification model based on absorption coefficient spectrum and refractive index spectrum shows good classification performance for redwood species and the accuracy rate of classification is 94% and 96% which can show that they can classify and identify redwood species correctly. THz-TDS technique is used to classify and identify mahogany, which provides a new idea and technical scheme for the classification and identification of mahogany therefore it can be used as a supplement to the near-infrared spectrum wood detection method. This method also provides a theoretical basis to apply terahertz technology in the field of wood classification and identification.