This paper discusses the gain in efficiency from including deforestation risk as a targeting criterion in payments for environmental services (PES) programs. We contrast two payment schemes that we simulate using data from Mexican common property forests: a flat payment scheme with a cap on allowable hectares per enrollee, similar to the program implemented in many countries, and a payment that takes deforestation risk and heterogeneity in land productivity into account. We simulate the latter strategy both with and without a budget constraint. Using observed past deforestation, we find that while risk-targeted payments are far more efficient, capped flat payments are more egalitarian. We also consider the characteristics of communities receiving payments from both programs. We find that the risk-weighted scheme results in more payments to poor communities, and that these payments are more efficient than those made to non-poor ejidos. Finally, we show that the risk of deforestation can be predicted quite precisely with indicators that are easily observable and that cannot be manipulated by the community.