In　the　past　decades,　radio-echo　sounding　(RES)　data　have　been　used　to　predict　basal　dry-wet　distributions　in　glaciated　regions　through　manual　inspection　of　the　records.　Extending　such　work,　we　propose　a　semiautomatic　method　for　predicting　such　distributions.　The　method　improves　previous　work　in　two　ways:　1)　subglacial　water　bodies　are　taken　as　a　reference　to　correct　the　thresholds　of　dry　and　wet　beds＇　identification　at　a　regional　scale　and　2)　five　distinct　features　are　defined　and　used　to　automatically　identify　the　dry-wet　transition,　allowing　a　classification　model　based　on　a　support　vector　machine.　To　demonstrate　its　effectiveness,　the　method　is　applied　to　airborne　RES　data　collected　in　recent　years　over　Princess　Elizabeth　Land　in　East　Antarctica.　A　comparative　analysis　of　the　new　versus　the　previous　method　was　carried　out　in　the　Ridge　B　region　of　East　Antarctica　and　at　the　Thwaites　Glacier　region　of　West　Antarctica.　The　results　show　that　the　method　can　obtain　more　accurate　subglacial　dry-wet　distribution　results　with　larger　coverage　and　has　the　potential　to　determine　dry-wet　transitions　at　a　continental　scale　if　applied　to　the　full　set　of　known　Antarctic　RES　data.