Predicting radioactive waste glass dissolution with machine learning

•Machine learning was applied to predict static/dynamic glass leaching behaviour.•Large-scale data was used with diverse experimental conditions and compositions.•Machine learning can accurately predict leaching within experimental error.•The bagged random forest method performs best for static leaching.•Dynamic leaching showed no preferred output concentration species (Si, Na, or Al).