In　order　to　estimate　the　urban　economic　losses　after　earthquakes,　builds　the　prediction　model　based　on　grey　relation　and　genetic　neural　network.　According　to　the　grey　correlation　analysis,　screens　out　the　major　factor　effecting　the　earthquake　losses　as　input　vectors　of　neural　network　first,　adopts　genetic　algorithm　to　optimize　the　initial　weights　and　bias　of　BP　network　and　then,　solves　the　problem　that　the　traditional　neural　network　has　slow　convergence　velocity　and　can　not　easy　to　get　the　global　optimum.　According　to　the　example,　we　can　get　the　model　that　has　good　forecast　accuracy　and　convergence　rate　and　checks　the　rationality　and　effectiveness　at　last.