Artisanal Small-scales Gold Mining (ASGM) which are using mercury as a gold solvent is still exposed in Indonesia recently. The purpose of this study was to predict the level of environmental pollution due to the presence of mercury in ASGM areas in several cities in Indonesia. This study used data mining techniques based on samples of mercury concentration data in groundwater, river water, sediment, soil, plants, biota (fish), and ambient air collected from 2018 to 2021 at ASGM areas that are still actively operated. The prediction model was using the Naïve Bayes algorithm which showed an accuracy of 99.1% and a Kappa value of 0.815 which illustrated that the level of agreement of the model is very strong. The study result describe the mercury content of each environmental media compared to the national quality standard showed that the areas with the highest levels of pollution were Lebak-Banten, while the areas with moderate and low levels of pollution were Simpenan-Sukabumi and Cineam-Tasikmalaya. A prediction model through visualization can provide an overview of the main factor causing high pollution in certain ASGM areas, namely the non-optimal process of transferring gold processing technology without mercury and the lack of awareness of the dangers of mercury. These factors can be used as evidence for preparing “Regional Action Plans for Mercury Reduction and Elimination”.