The　peak　of　short-circuit　current　is　of　great　importance　for　selective　protection　of　low-voltage　distribution　system　and　reliable　breaking　of　circuit　breaks.　However,　it　is　lack　of　intensive　study　now.　Based　on　the　early　fault　detection　technology　and　the　parameters　analyzed　by　simulation,　this　paper　concludes　the　main　factors　which　influence　the　peak　value　by　using　grey　correlation　degree.　Furthermore,　the　extreme　learning　machine　(ELM)　is　used　to　forecast　the　peak　value　of　fault　current.　Simulation　results　show　that　the　grey　correlation　degree　can　identify　the　main　factors　of　the　short-circuit　current　effectively.　And　it　can　also　reduce　the　dimensions　of　characteristic　variable　of　short-circuit　current.　Finally,　the　short-circuit　current　prediction　method　based　on　the　early　fault　detection　and　extreme　learning　machine　shows　strong　robustness　and　high　precision,　which　can　lay　the　foundation　for　the　realization　of　low-voltage　selective　protection　technology.　©　2016,　Power　System　Protection　and　Control　Press.　All　right　reserved.