Bankruptcy　prediction　has　long　been　a　significant　issue　in　finance　and　management　science,　which　attracts　the　attention　of　researchers　and　practitioners.　With　the　great　development　of　modem　information　technology,　it　has　evolved　into　using　machine　learning　or　deep　learning　algorithms　to　do　the　prediction,　from　the　initial　analysis　of　financial　statements.　In　this　paper,　we　will　review　the　machine　learning　or　deep　learning　models　used　in　bankruptcy　prediction,　including　the　classical　machine　learning　models　such　as　Multivariant　Discriminant　Analysis　(MDA),　Logistic　Regression　(LR),　Ensemble　method,　Neural　Networks　(NN)　and　Support　Vector　Machines　(SVM),　and　major　deep　learning　methods　such　as　Deep　Belief　Network　(DBN)　and　Convolutional　Neural　Network　(CNN).　In　each　model,　the　specific　process　of　experiment　and　characteristics　will　be　summarized　through　analyzing　some　typical　articles.　Finally,　possible　innovative　changes　of　bankruptcy　prediction　and　its　future　trends　will　be　discussed.　(C)　2020　The　Authors.　Published　by　Elsevier　B.V.