Near-infrared (NIR) spectroscopy has been utilized to assess hyaline cartilage quality in human and animal osteochondral tissues. However, due to the lack of NIR signal from bone phosphate, and the relatively deep penetration depth of the radiation, the separate contributions of cartilage and bone to the spectral signatures have not been well defined. The objectives of the current study were 1) to improve the understanding of the contributions of bone and cartilage to NIR spectra acquired from osteochondral tissue, and 2) to assess the ability of this non-destructive method to predict cartilage thickness and modified Mankin grade of human tibial plateau articular cartilage. NIR spectra were acquired from samples of bovine bone and cartilage with varying thicknesses, and from twenty-two tibial plateaus harvested from patients undergoing knee replacement surgery. Spectra were recorded from regions of the tibial plateaus with varying degrees of degradation, and the cartilage thickness and modified Mankin grade of these regions were assessed histologically. Spectra from bone and cartilage samples of known thicknesses were investigated to identify spectral regions that were distinct for these two tissues. Univariate and multivariate linear regression methods were used to correlate modified Mankin grade and cartilage thickness with NIR spectral changes. The ratio of the NIR absorbances associated with water at 5270 and 7085 cm−1 were the best differentiator of cartilage and bone spectra. NIR prediction models for thickness and Mankin grade calculated using partial least squares regression were more accurate than univariate-based prediction models, with root mean square errors of cross validation of 0.42 mm (thickness) and 1.3 (modified Mankin grade), respectively. We conclude that NIR spectroscopy may be used to simultaneously assess articular cartilage thickness and modified Mankin grade, based in part on differences in spectral contributions from bone and cartilage.