Walking　time　prediction　aims　to　deduce　waiting　time　and　travel　time　for　passengers　and　provide　a　quantitative　basis　for　the　subway　schedule　management.　This　model　is　founded　based　on　transfer　passenger　flow　and　type　of　pedestrian　facilities.　Chaoyangmen　station　in　Beijing　was　taken　as　the　learning　set　to　obtain　the　relationship　between　transfer　walking　speed　and　passenger　volume.　The　sectional　passenger　volume　of　different　facilities　was　calculated　related　to　the　transfer　passage　classification.　Model　parameters　were　computed　by　curve　fitting　with　respect　to　various　pedestrian　facilities.　The　testing　set　contained　four　transfer　stations　with　large　passenger　volume.　It　is　validated　that　the　established　model　is　effective　and　practical.　The　proposed　model　offers　a　real-time　prediction　method　with　good　applicability.　It　can　provide　transfer　scheme　reference　for　passengers,　meanwhile,　improve　the　scheduling　and　management　of　the　subway　operation.