Community forestry (CF) is increasingly used in developing countries to achieve both the socioeconomic outcome of poverty reduction and an ecological outcome. There have been many single case studies in a specific region to identify the factors affecting the success or failure of CF. Other studies have used large-N data collected from multiple countries. However, there is a dearth of large-N studies within a single country. In this study, we used a country scale dataset of 197 CF projects, established between 1994 and 2005 across Cambodia, to identify the biophysical factors that affected forest cover changes from 2005 to 2016. A mixed-effects logistic regression model was used for a total of 71,252 randomly sampled data pixels nested in the 197 CF. Results showed that deforestation in CF was likely to increase with increasing size of CF area at lower elevations and on gentler slopes. Deforestation also increased if CF was located close to villages, markets and CF boundaries, but further away from main roads. These findings on biophysical factors can help the government to decide on priority locations for further conservation interventions or for the establishment of new CF projects.