Rheumatoid arthritis (RA) is a common chronic and systemic autoimmune diseases that cause inflammation of the thin layer of tissue lining the joints. Interleukin-6 (IL-6), along with TNF-a and several inflammatory cytokines, acts a vital role in activation of local synovial leukocyte production and induction of chronic inflammation. A humanized anti-IL-6 receptor(IL-6R) monoclonal antibody, Tocilizumab (TCZ), has been demonstrated a significant clinical efficacy for RA patients. However, like other inflammatory cytokine blockers such as TNF-a, Interleukin-1 (IL-1), or CD20 inhibitors, some patients still show a partial respond or resistant to the treatment. This study therefore aimed at identifying protein biomarkers that could predict clinical response against TCZ in RA patients by implementing high-precision proteomics approach. We first identified 54 serum protein biomarker candidates from a large-scale serum proteome profiling of TCZ responder and non-responder groups. Selected protein biomarker candidates combined with known RA biomarkers from the literature data mining were verified by two different targeted quantification methods; multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) with Triple-quadrupole (QqQ) and Q-Exactive (QE), respectively. Moreover, we validated the results with 47 individual serum samples using MRM and developed as a multi-biomarker panel. The constructed 4-biomarker panel showed 83% discriminate power in average between two different groups with high AUC value of 0.859. The panel also shows 82% sensitivity and 84% specificity of its innate validity. Collectively, our multi-biomarker panel implies that 4 selected proteins were able to serve as diagnostic assessments to predict the TCZ non-responders in RA patients and possible to supplement serum biomarker discovery-validation process in the clinical field based on integrative proteomic approach.