In　this　paper,　we　present　a　novel　3-D　oral　shape　retrieval　using　correntropy-based　registration　algorithm.　Fast　matching　as　the　traditional　registration　method　can　achieve,　its　registration　accuracy　is　disturbed　by　noise　and　outliers.　Since　the　3-D　oral　model　contains　a　large　amount　of　noise　and　outliers,　it　may　lead　to　a　decrease　in　registration　accuracy,　which　affects　the　accuracy　of　retrieval　rate.　Therefore,　we　introduce　the　correntropy　into　the　rigid　registration　algorithm　to　solve　this　problem.　Although　the　noise　and　outliers　are　suppressed　by　the　correntropy-based　algorithm,　these　noises　and　outliers　still　participate　in　the　registration.　For　better　retrieval,　we　choose　the　matched　point　cloud　data　and　use　mean　squared　error　results　to　judge　the　individual　differences　of　the　shape.　Finally,　the　accurate　retrieval　of　the　oral　shape　is　realized.　Experimental　results　demonstrate　our　3-D　shape　retrieval　algorithm　can　be　successfully　searched　under　different　models,　which　can　help　forensics　use　the　characteristics　of　biological　individuals　to　accurately　search　and　identify,　and　improve　recognition　efficiency.　©　2020,　Springer　Nature　Switzerland　AG.