The current proof-of-principle study was aimed toward development of a novel multidimensional protein identification technology (MudPIT) approach for the in-depth proteome analysis of human serum derived from patients with benign prostate hyperplasia (BPH) using rational chromatographic design principles. This study constituted an extension of our published work relating to the identification and relative quantification of potential clinical biomarkers in BPH and prostate cancer (PCa) tissue specimens. The proposed MudPIT approach encompassed the use of three distinct yet complementary liquid chromatographic chemistries. High-pressure size-exclusion chromatography (SEC) was used for the prefractionation of serum proteins followed by their dialysis exchange and solution phase trypsin proteolysis. The tryptic peptides were then subjected to offline zwitterion−ion hydrophilic interaction chromatography (ZIC-HILIC) fractionation followed by their online analysis with reversed-phase nano-ultraperformance chromatography (RP-nUPLC) hyphenated to nanoelectrospray ionization-tandem mass spectrometry using an ion trap mass analyzer. For the spectral processing, the sequential use of the SpectrumMill, Scaffold, and InsPecT software tools was applied for the tryptic peptide product ion MS² spectral processing, false discovery rate (FDR) assessment, validation, and protein identification. This milestone serum analysis study allowed the confident identification of over 1955 proteins (p ≤ 0.05; FDR ≤ 5%) with a broad spectrum of biological and physicochemical properties including secreted, tissue-specific proteins spanning approximately 12 orders of magnitude as they occur in their native abundance levels in the serum matrix. Also encompassed in this proteome was the confident identification of 375 phosphoproteins (p ≤ 0.05; FDR ≤ 5%) with potential importance to cancer biology. To demonstrate the performance characteristics of this novel MudPIT approach, a comparison was made with the proteomes resulting from the immunodepletion of the high abundant albumin and IgG proteins with offline first dimensional tryptic peptide separation with both ZIC-HILIC and strong cation exchange (SCX) chromatography and their subsequent online RP-nUPLC−nESI-MS² analysis.