Fault localization problem is one of the most difficult processes in software debugging. Several spectrum-based ranking metrics have been proposed and none is shown to be empirically optimal. In this paper, we consider the fault localization problem as a multicriteria decision making problem. The proposed approach tackles the different metrics by aggregating them into a single metric using a weighted linear formulation. A learning step is used to maintain the right expected weights of criteria. This approach is based on Analytic Hierarchy Process (AHP), where a ranking is given to a statement in terms of suspiciousness according to a comparison of ranks given by the different metrics. Experiments performed on standard benchmark programs show that our approach enables to propose a more precise localization than existing spectrum-based metrics.