Nowadays, most organizations have adopted IT outsourcing (ITO) into their main business strategy as it promises several benefits such as cost reduction, staff ability improvement and technology enhancement. Supplier selection is a key essential process in ITO. Unfortunately, supplier selection is a complex decisionmaking process as the evaluation involved with multi criteria and each criterion carries a different weight. Usually, the weight for each criterion is assigned by experts which might introduce uncertainty, bias, and opaqueness. Therefore, this paper proposed a hybrid method that aimed to eliminate human roles in determining evaluation criteria weight during supplier selection process. The method was designed by integrating Firefly Algorithm (FA) into Analytic Hierarchy Process (AHP) and termed as Firefly Algorithm Analytic Hierarchy Process (FAHP). It is operationalized on three datasets which were obtained from the referenced literature. Experimental results showed that the obtained Consistency Ratio (CR) value (i.e. 0.001) and Sum of Bias (SB) value (i.e. 0.351) are very close to zero. These findings show that the proposed FAHP is feasible to identify relevant supplier even though the criteria weight was determined without human involvement. Such an approach reduces human bias throughout AHP synthesis process. Consequently, the obtained weights were the optimal solution that can be adopted in the supplier selection problem.