Calycophyllum spruceanum (Benth) is a tree of the Amazon region popularly known as ‘mulateiro’, whose wood has multiple uses, from energy to folk medicine. Thus, it is extremely important to evaluate desirable characteristics, through quick methods that meet the principles of green chemistry. The objective of this study was to evaluate the potential of the near-infrared (NIR) spectroscopy technique for the prediction of dry matter, carbon and ash contents and identification of parts of C. spruceanum trees. The Partial Least Squares (PLS) regression model applied within the spectral range of 400–2498 nm proved to be adequate to estimate the dry matter, carbon and ash contents in C. spruceanum sapwood and bark samples, with R2 above 0.90 in both calibration and validation. Hierarchical cluster analysis and principal component analysis techniques when applied to the spectra were able to efficiently separate bark from sapwood. The results show that the NIR technique developed can be used in the determination of dry matter, carbon and ash contents in C. spruceanum, in addition to its discriminatory power in the separation of parts of the plant.