Membranous nephropathy is one of the most common causes of primary glomerular diseases worldwide. The present study adopted a gel-based proteomics approach to better understand the pathophysiology and define biomarker candidates of human membranous nephropathy using an animal model of passive Heymann nephritis (PHN). Clinical characteristics of Sprague-Dawley rats injected with rabbit anti-Fx1A antiserum mimicked those of human membranous nephropathy. Serial urine samples were collected at Days 0, 10, 20, 30, 40, and 50 after the injection with anti-Fx1A (number of rats = 6; total number of gels = 36). Urinary proteome profiles were examined using 2D-PAGE and SYPRO Ruby staining. Quantitative intensity analysis and ANOVA with Tukey post-hoc multiple comparisons revealed 37 differentially expressed proteins among 6 different time-points. These altered proteins were successfully identified by MALDI-TOF MS and classified into 6 categories: (i) proteins with decreased urinary excretion during PHN; (ii) proteins with increased urinary excretion during PHN; (iii) proteins with increased urinary excretion during PHN, but which finally returned to basal levels; (iv) proteins with increased urinary excretion during PHN, but which finally declined below basal levels; (v) proteins with undetectable levels in the urine during PHN; and (vi) proteins that were detectable in the urine only during PHN. Most of these altered proteins have functional significance in signaling pathways, glomerular trafficking, and controlling the glomerular permeability. The ones in categories (v) and (vi) may serve as biomarkers for detecting or monitoring membranous nephropathy. After normalization of the data with 24-h urine creatinine excretion, changes in 34 of initially 37 differentially expressed proteins remained statistically significant. These data underscore the significant impact of urinary proteomics in unraveling disease pathophysiology and biomarker discovery.