One of the key goals of social forestry is to involve the poor as project beneficiaries. It is possible to measure the degree of attainment of this goal by collecting socioeconomic data before and after project implementation. This approach cannot be applied at the many sites where ex-ante data were never gathered. This article proposes a methodology for evaluating the degree of inclusion of the poor in social forestry using ex-post data alone. Longitudinal analysis is approximated through the use of 'slow change' socioeconomic variables and through logistic regression. The methodology is illustrated with data on the Java Social Forestry Program.