This study employed a quantile regression model as a machine learning tool in Python to assess the nuanced effects and relationships within a dataset examining the combined impact of Internet connectivity and degrees of economic freedom on global corruption. The study uses a dataset covering 161 nations from 2010 to 2019, incorporating various sources of information for a range of variables rooted in theory. The findings suggest an influence of the combination of greater freedom and internet access in countering corruption. Consequently, policies that focus on improving the availability of open information, online social networking, and other elements linked to Internet accessibility should be considered as a practical approach to curbing corruption within the countries examined.