Heavy metal exposure is acknowledged as a risk factor for poor health. However, the effect of heavy metal exposure on the prevalence of gallstones is still unknown. Therefore, we investigated the relationship between heavy metal concentrations and the prevalence of gallstones among US adults. Multivariate logistic regression indicated that only urinary cadmium was an independent risk factor for gallstones. Compared to the low urine cadmium group, the high cadmium group had a elevated increased risk of gallstone formation. Furthermore, the weighted quantile sum model showed that heavy metal mixtures were not associated with gallstone prevalence. Additionally, urinary cadmium levels were associated with an increased risk of gallstone formation in young individuals, males, Mexican Americans, Non-Hispanic Whites, as well as smokers and drinkers. Moreover, nine machine learning methods were utilized to construct an interpretable predictive model for gallstone prevalence. Among these models, the XGBoost model exhibited the highest performance and was selected for further investigation. Subsequently, shapely additive explanations was used for model interpretation. The results also indicated that urinary cadmium concentrations were the most important variable for gallstones. Thus, our results indicated that long-term chronic cadmium exposure is a risk factor for gallstone prevalence.