To establish a serological classification tree model for rheumatoid arthritis (RA), protein/peptide profiles of serum were detected by matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange (WCX) from Cohort 1, including 65 patients with RA and 41 healthy controls (HC). The samples were randomly divided into a training set and a test set. Twenty-four differentially expressed peaks (P < 0.05) were identified in the training set and 4 of them, namely m/z 3,939, 5,906, 8,146, and 8,569 were chosen to set up our model. This model exhibited a sensitivity of 100.0% and a specificity of 96.0% for differentiating RA patients from HC. The test set reproduced these high levels of sensitivity and specificity, which were 100.0 and 81.2%, respectively. Cohort 2, which include 228 RA patients, was used to further verify the classification efficiency of this model. It came out that 97.4% of them were classified as RA by this model. In conclusion, MALDI-TOF-MS combined with WCX magnetic beads was a powerful method for constructing a classification tree model for RA, and the model we established was useful in recognizing RA.