Recent advances in “omics” technologies have opened the possibilities to discover novel biomarkers of meat quality, including the early detection of quality defects such as dark-cutting beef, also known as DFD (dark, firm, and dry) beef characterized by a high ultimate pH. The available studies characterized very few numbers of animals and using mostly gel-based proteomics. The present study uses for the first time a Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) proteomics approach to characterize and comprehensively quantify the post-mortem muscle proteomes of DFD (pH24 ≥ 6.2) compared to CONTROL beef samples (5.4 ≤ pH24 ≤ 5.6) within the largest database of DFD/CONTROL beef samples to date (26 pairs of samples of the young Asturiana de los Valles bulls, n=52). The statistical comparison yielded 35 putative protein biomarkers that significantly differed in their abundances between the DFD and CONTROL samples. Chemometrics methods using both PLS-DA and OPLS-DA applied on the proteome data revealed 31 and 36 proteins with VIP > 2 respectively. The combination of these findings identified 16 common proteins linked with DFD beef, irrespective of the statistical method. These proteins are associated with interconnected biochemical pathways related to energy metabolism (DHRS7B and CYB5R3), binding and signaling (RABGGTA, MIA3, BPIFA2B, CAP2, APOBEC2, UBE2V1, KIR2DL1), muscle contraction, structure and associated proteins (DMD, PFN2), proteolysis, hydrolases, and activity regulation (AGT, C4A, GLB1, CAND2), and calcium homeostasis (ANXA6). These results evidenced the potential of SWATH-MS and chemometrics to accurately identify novel biomarkers for meat quality defects, providing a deeper understanding of the molecular mechanisms underlying dark-cutting beef.