Adding　antifreeze　filler　to　the　asphalt　mixture　can　make　the　road　surface　have　a　certain　automatic　snow-melting　function,　but　the　snow-melting　effect　of　antifreeze　asphalt　pavement　(AFAP)　is　greatly　affected　by　the　environment.　To　ensure　that　road　management　can　take　other　snow-melting　measures　in　a　timely　manner　when　the　road　surface　cannot　melt　snow,　an　early-warning　model　of　AFAP　was　studied.　To　conduct　a　comparative　analysis　the　freezing　time　under　different　environmental　factors,　ordinary　asphalt　pavement　(OAP)　and　AFAP　were　used　as　subjects.　The　test　results　show　that　the　temperature,　humidity,　and　precipitation　significantly　impact　the　freezing　time　of　pavement.　A　feature　matrix　of　environmental　factors　was　established　by　preprocessing　the　experimental　data.　After　initially　building　the　model　and　parameter　tuning,　an　ice　warning　model　for　AFAP　under　multifactor　conditions　using　support　vector　machines　(SVMs)　was　constructed.　Additionally,　the　model　was　used　to　predict　the　freezing　time　under　different　environmental　factors.　The　prediction　model　based　on　the　SVM　could　accurately　predict　the　freezing　time　and　has　a　high　generalization　ability.　The　research　results　provide　a　solution　to　early　icing　warnings　for　AFAP　under　specified　scenarios.　　©　2025　American　Society　of　Civil　Engineers.