Rapidly developing proteomic tools are improving detection of deregulated kallikrein-related peptidase (KLK) expression, at the protein level, in prostate and ovarian cancer, as well as facilitating the determination of functional consequences downstream. MS-driven proteomics uniquely allows for the detection, identification, and quantification of thousands of proteins in a complex protein pool, and this has served to identify certain KLKs as biomarkers for these diseases. In this review, we describe applications of this technology in KLK biomarker discovery and elucidate MS-based techniques that have been used for unbiased, global screening of KLK substrates within complex protein pools. Although MS-based KLK degradomic studies are limited to date, they helped to discover an array of novel KLK substrates. Substrates identified by MS-based degradomics are reported with improved confidence over those determined by incubating a purified or recombinant substrate and protease of interest, in vitro. We propose that these novel proteomic approaches represent the way forward for KLK research, in order to correlate proteolysis of biological substrates with tissue-related consequences, toward clinical targeting of KLK expression and function for cancer diagnosis, prognosis, and therapies.