Cashmere plays an important role in luxury fashion due to its characteristics of fineness, warmth, and softness. In the frame of "green economy", many companies have started to produce and market recycled cashmere textiles. Recycled cashmere is derived from postfactory and post-consumer waste. The mechanical action involved in recycling cashmere causes severe damage to the fibers, affecting their morphological and mechanical properties. In order to safeguard the consumers and the companies from possible adulteration, a correct identification of fibers is required. NIR spectroscopy was applied to analyze and distinguish virgin and recycled cashmere fibers. Because no significant differences can be seen in the recorded spectra, the principal component analysis (PCA) combined with the soft independent modeling class analogy (SIMCA) method allows the classification of fibers into two distinct classes, leading to a sure identification of recycled and virgin cashmere. A calibration curve was also performed in order to quantify recycled cashmere fibers in a blend with virgin ones. The interclass distance in the SIMCA method was found to be 249.77, whereas the results from quantitative calibration show a standard error of prediction value of 5.8% w/w (for a mean value of 50% w/w). Microscopy analysis was also carried out to confirm the origin of the recycled cashmere. These preliminary results confirmed that the NIR spectroscopy coupled with chemometric methods might be a useful tool for the rapid screening of recycled cashmere fibers and their raw quantification in a blend.