The major goal of social policy in most developing countries is poverty alleviation. The ultimate challenge for policymakers is to use the available resources of the Government in order to provide the greatest possible assistance to those who need it most. Geographical targeting has emerged as one of the more feasible and efficient targeting methods. However, its full utilization is seriously hampered by the lack of the needed data sets. On the other hand, new computational approaches have great potential in providing spatially-disaggregate information. The paper explores the application of small area estimation and spatial microsimulation methods in geographical targeting.