The Highly Pathogenic Avian Influenza H5N1 (HPAI) virus is now considered endemic in several Asian countries. In Cambodia, the virus has been circulating in the poultry population since 2004, with a dramatic effect on farmers' livelihoods and public health. In Thailand, surveillance and control are still important to prevent any new H5N1 incursion. Risk mapping can contribute effectively to disease surveillance and control systems, but is a very challenging task in the absence of reliable disease data. In this work, we used spatial multicriteria decision analysis (MCDA) to produce risk maps for HPAI H5N1 in poultry. We aimed to i) evaluate the performance of the MCDA approach to predict areas suitable for H5N1 based on a dataset from Thailand, comparing the predictive capacities of two sources of a priori knowledge (literature and experts), and ii) apply the best method to produce a risk map for H5N1 in poultry in Cambodia. Our results showed that the expert-based model had a very high predictive capacity in Thailand (AUC¿=¿0.97). Applied in Cambodia, MCDA mapping made it possible to identify hotspots suitable for HPAI H5N1 in the Tonlé Sap watershed, around the cities of Battambang and Kampong Cham, and along the Vietnamese border.