We hypothesized that corruption could contribute to deforestation. The present study, therefore, try to identify such a relation between corruption and deforestation. By using three different corruption indices, we found a statistically significant strong positive relation between corruption and deforestation for different periods across different countries. This finding remains valid in both univariate and multivariate models. Also, the model takes the potential heteroscedasticity problem, common in cross-section studies, into account and makes correction if necessary. To our best knowledge, this study is the first cross-country study addressing to the issue by utilizing all available corruption indices, namely Corruption Perception Index (CPI), International Country Risk Guide (ICRG) index, and Business Intelligence (BI) index. Policies and measures taken towards reducing corruption, therefore, may help to decrease illegal forest activities (e.g. illegal logging and timbering, smuggling of forest products etc.) and in turn depletion of forests.