Currently existing objective methods to evaluate tenderness and chewiness of pork in general do not yield satisfactory correlation to sensory panel evaluations, and their applications in meat industry are hence limited. In this study, a Raman spectrosensing method was developed to evaluate and predict tenderness and chewiness of pork loins. Raman spectroscopic binary barcodes for pork loins from 169 pigs were created based on their spectroscopic characteristics, and multivariate statistical discriminant model was developed based on the Raman barcodes to differentiate and classify pork loins into tenderness grades. Good agreement (> 82% correct predictions) with sensory panel results were obtained especially for pork loins that were at the extreme ends of tenderness (tenderness score < 8 or > 11) and chewiness (chewiness score < 2 and > 4) spectrum. The method developed in this report has the potential to become a rapid objective assay for tenderness and chewiness of pork products that may find practical applications in pork industry.