Kiwifruit is one of the fruits with strong development momentum and economic benefits in China, its pulp color has become an important indicator for evaluating the quality of kiwifruit. Here, near-infrared spectroscopy was employed to study the changes in pulp color in different depths of kiwifruit during different storage periods. In this study, the “Mute” kiwifruit’s pulp color features (L*, a*, b*) in depths of 0, 5, and 10 mm under the skin wereviewed as the research object, the near-infrared spectroscopy (830～2 500 nm) was used as a technical tool, and chemometric methods were combined to analyze the pulp color features of kiwifruit. By establishing a partial least-square regression (PLSR) model based on the full-wavelengths, it found that the established model offered good results by using color features (L*5, a*5, b*5) at a depth of 5 mm, which indicated that the pulp color features and the spectrum data had a relatively high correlation. Then, the competitive adaptive reweighted sampling (CARS) and uninformative variable elimination (UVE) algorithms were used to select the characteristic wavelengths related to color features from the high-dimensional full-wavelengths. And the PLSR and multiple linear regression (MLR) prediction models were respectively established based on the color features (L*5, a*5, b*5) and spectra at characteristic wavelengths. Results revealed that the CARS-PLSR model with the RC=0.942 7, RMSEC=1.699 7, RP=0.885 0, and RMSEP=1.642 4 has the best predictive effect for the pulp color feature L*5; the UVE-MLR model with the RC=0.946 3, RMSEC=0.342 4, RP=0.854 9, and RMSEP of 1.354 3 exhibited the best predictive results for pulp color feature a*5, the CARS-MLR model with the RC=0.944 3, RMSEC=1.010 1, RP=0.839 8, and RMSEP=1.354 3 performed best predictive results for pulp color feature b*5. The results demonstrated that the near-infrared spectroscopy technique would be employed to detect the color features at different depths of kiwifruit, which provided technical support for the quality evaluation of kiwifruit.