The　influencing　factors　of　aluminum　electrolysis　production　process　are　complex,　and　current　efficiency　is　an　important　evaluation　index.　In　order　to　study　the　influence　of　various　parameters　on　the　current　efficiency　in　the　aluminum　electrolysis　production　process,　a　LightGBM-TPE　current　efficiency　optimization　model　was　established　in　this　paper.　First,　the　production　data　is　preprocessed,　and　the　industrial　parameters　are　fitted　using　the　LightGBM　prediction　model.　Then,　to　further　increase　the　model＇s　prediction　accuracy,　the　TPE　optimization　method　is　used　to　optimize　the　LightGBM　hyperparameters.　Finally,　the　optimization　of　current　efficiency　is　realized　through　Optuna　combined　with　TPE　Bayesian　optimization　algorithm.　The　experimental　results　demonstrate　that　the　model　is　capable　of　accurately　identifying　the　realization　conditions　and　process　parameters　of　high　current　efficiency　in　the　production　process,　as　well　as　providing　a　parameter　control　foundation　for　the　effective　operation　of　the　actual　electrolytic　aluminum　production,　ultimately　achieving　the　goal　of　power　consumption　reduction.　©　2023　SPIE.