Coliform mastitis remains a primary focus of dairy cattle disease research due in part to the lack of efficacious treatment options for the deleterious side effects of exposure to LPS, including profound intra-mammary inflammation. To facilitate new veterinary drug approvals, reliable biomarkers are needed to evaluate the efficacy of adjunctive therapies for the treatment of inflammation associated with coliform mastitis. Most attempts to characterize the host response to LPS, however, have been accomplished using ELISAs. Because a relatively limited number of bovine-specific antibodies are commercially available, reliance on antibodies can be very limiting for biomarker discovery. Conversely, proteomic approaches boast the capability to analyze an unlimited number of protein targets in a single experiment, independent of antibody availability. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), a widely used proteomic strategy for the identification of proteins in complex mixtures, has gained popularity as a means to characterize proteins in various bovine milk fractions, both under normal physiological conditions as well as during clinical mastitis. The biological complexity of bovine milk has, however, precluded the complete annotation of the bovine milk proteome. Conventional approaches to reducing sample complexity, including fractionation and the removal of high abundance proteins, has improved proteome coverage, but the dynamic range of proteins present, and abundance of a relatively small number of proteins, continues to hinder comparative proteomic analyses of bovine milk. Nonetheless, advances in both liquid chromatography and mass spectrometry instrumentation, including nano-flow liquid chromatography (nano-LC), nano-spray ionization, and faster scanning speeds and ionization efficiency of mass spectrometers, have improved analyses of complex samples. In the current paper, we review the proteomic approaches used to conduct comparative analyses of milk from healthy cows and cows with clinical mastitis, as well as proteins related to the host response that have been identified in mastitic milk. Additionally, we present data that suggests the potential utility of LC-MS/MS label-free quantification as an alternative to costly labeling strategies for the relative quantification of individual proteins in complex mixtures. Temporal expression patterns generated using spectral counts, an LC-MS/MS label-free quantification strategy, corresponded well with ELISA data for acute phase proteins with commercially available antibodies. Combined, the capability to identify low abundance proteins, and the potential to generate temporal expression profiles, indicate the advantages of using proteomics as a screening tool in biomarker discovery analyses to assess biologically relevant proteins modulated during disease, including previously uncharacterized targets.