Such as prospective studies can provide evidence-based information for clinicians and regulatory agencies, modelling studies provide useful information when experimental studies are to complex, too long, or too expensive to carry out. If modelling has been widely used in pharmacokinetics, it is in the field of pharmacoeconomics that numerous models have been published in recent years, including models relevant to the management of rheumatoid arthritis (RA). The most common modelling techniques published in RA are decision trees and Markov models which are used to perform cost-effectiveness and cost-utility analyses using real or simulated populations. This paper reviews the main types of modelling techniques used in pharmacoeconomic studies with the aim of clarifying their interest and limitations for the clinicians. Generating such evidence is highly relevant to assisting clinical recommendations and reimbursement decisions towards enabling the optimal management of RA and reducing its overall clinical and economic burden, for the benefits of patients and health systems.