Estimation of urban vulnerability to natural hazards such as earthquakes can be considered as an ill-structured problem (i.e. a problem for which there is no unique, identifiable, objectively optimal solution). This paper outlines developing a spatial decision support system (SDSS) to assist earthquake vulnerability assessment. There are different criteria in characterizing real world for disaster management. This paper addresses a suitable method for weighing different related factors affecting in decision making process and managing uncertainties of defined factors which is inherited from reality. These two problems, especially the latter, result in biases in decisions. The proposed solution could be uncertainty absorption, evaluation and documentation at each step, especially in real world characterization and hypotheses derivation. This research deals with such treatment for weighing and normalizing contributed factors in vulnerability of cities' population against earthquakes using analytic hierarchy process (AHP) method. The results shown that this method provide high degree of analytical capabilities and can be used as the basis for further research due to introduction of other effective factors such as social and economic situations) in earthquakes' vulnerability.