The　information　of　the　acute　oral　toxicity　for　most　polycyclic　aromatic　hydrocarbons　(PAHs)　in　mammals　are　lacking　due　to　limited　experimental　resources,　leading　to　a　need　to　develop　reliable　in　silico　methods　to　evaluate　the　toxicity　endpoint.　In　this　study,　we　developed　the　quantitative　structure-activity　relationship　(QSAR)　models　by　genetic　algorithm　(GA)　and　multiple　linear　regression　(MLR)　for　the　rat　acute　oral　toxicity　(LD50)　of　PAHs　following　the　strict　validation　principles　of　QSAR　modeling　recommended　by　OECD.　The　best　QSAR　model　comprised　eight　simple　2D　descriptors　with　definite　physicochemical　meaning,　which　showed　that　maximum　atom-type　electrotopological　state,　van　der　Waals　surface　area,　mean　atomic　van　der　Waals　volume,　and　total　number　of　bonds　are　main　influencing　factors　for　the　toxicity　endpoint.　A　true　external　set　(554　compounds)　without　rat　acute　oral　toxicity　values,　and　22　limit　test　compounds,　were　firstly　predicted　along　with　reliability　assessment.　We　also　compared　our　proposed　model　with　the　OPERA　predictions　and　recently　published　literature　to　prove　the　prediction　reliability.　Furthermore,　the　interspecies　toxicity　(iST)　models　of　PAHs　between　rat　and　mouse　were　also　established,　validated　and　employed　for　filling　data　gap.　Overall,　our　developed　models　should　be　applicable　to　new　or　untested　or　not　yet　synthesized　PAHs　falling　within　the　applicability　domain　(AD)　of　the　models　for　rapid　acute　oral　toxicity　prediction,　thus　being　important　for　environmental　or　personal　exposure　risk　assessment　under　regulatory　frameworks.