Endocrine　disrupting　chemicals　(EDCs)　threaten　the　reproductive　fitness　of　aquatic　organisms　at　concentrations　lower　than　those　associated　with　longevity　and　development.　However,　the　small　number　of　aquatic　species　assessed　for　reproductive　toxicity　has　limited　the　ecological　risk　assessment　of　EDCs,　making　sensible　decisions　more　difficult.　In　response　to　this,　interspecies　correlation　estimation　(ICE)　models　were　established　for　EDCs　to　enable　the　estimation　of　reproduction　toxicity　values　to　a　wider　range　of　organisms.　A　total　of　16　ICE　models　of　EDCs　for　6　surrogate　species　were　statistically　significant.　Of　the　16　models,　37.5%　(6　models)　had　a　cross-validation　success　rate　＞　60%,　with　a　relatively　small　model　squared　error,　indicating　that　the　model　fit　is　robust.　These　model　results　implied　that　the　action　of　EDCs　for　each　species　pair　might　involve　the　same　mechanisms,　and　taxonomic　relationships　did　not　influence　the　prediction　precision.　The　cross-validation　success　rate　corroborated　the　consistency　between　the　projected　and　experimental　values　for　the　EDC　ICE　models.　Sixty-seven　percent　of　the　projected　values　fell　within　a　10-fold　difference　of　the　experimental　data.　The　results　indicated　that　a　proven　ICE　model　can　greatly　increase　the　amount　of　EDCs　chronic　toxicity　data　for　predicted　species,　without　the　need　for　extensive　animal　experiments,　thus　providing　substitute　chronic　toxicity　data　for　rapid　assessment　of　EDCs　ecological　risks.　(C)　2019　Elsevier　Ltd.　All　rights　reserved.