Behcet's Disease (BD) is a multisystem autoimmune disorder that lacks sensitive and specific diagnostic methods. The aim of this study was to identify potential biomarkers specific for BD and to establish a diagnostic model. Serum samples from patients with BD, Vogt-Koyanagi-Harada syndrome (VKH), and healthy controls (HC) were randomly divided into a training set (49 BD, 31 VKH, and 48 HC) and a testing set (13 BD, 10 VKH, and 11 HC). Proteomic mass spectra were generated by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Thirty-nine differential m/z peaks associated with BD were identified, and the m/z peaks at 1,644, 1,711, 2,023, 4,347, 6,628, and 8,559 were used to construct a model for the diagnosis of BD. This diagnostic model can distinguish BD from non-BD controls with a sensitivity of 83.67% (41/49) and a specificity of 89.87% (71/79). BD was detected in our blinded testing set with good sensitivity and specificity of 84.6 and 90.48%, respectively. The results suggested that proteomic fingerprint technology combining magnetic beads with MALDI-TOF-MS has potential for the diagnosis of BD. The biomarker classification model was suitable for preliminary identification of BD and could potentially serve as a useful tool for BD diagnosis and differential diagnosis. Anat Rec, 2012. © 2012 Wiley Periodicals, Inc.