Window　opening　behavior　significantly　impacts　indoor　air　quality,　thermal　comfort,　and　energy　consumption.　A　field　measurement　was　carried　out　in　three　typical　rooms　(a　standard　office,　a　meeting　room　and　a　smoking　office)　within　an　office　building.　The　window　state　and　the　physical　environment　were　continuously　recorded　during　the　measured　periods.　Three　typical　window　opening　behaviors　were　found　in　the　measured　samples,　namely,　active,　moderate,　and　passive.　The　common　logistic　regression　coefficient　indicated　that　solar　radiation　exhibited　the　greatest　effect　on　window　opening　behavior　in　the　smoking　office　and　standard　office.　Typically,　window　opening　behavior　in　the　meeting　room　was　the　most　strongly　correlated　with　time　of　the　day,　mainly　because　of　the　meeting　schedule　for　occupants　in　the　meeting　room.　This　study　discussed　the　dividing　principles　involved　in　setting　the　dummy　variable　interval　level　(discretizing　continuous　variables　and　dividing　them　into　different　intervals),　and　proposed　a　method　to　determine　the　optimal　interval　level　of　each　variable.　The　improved　model　led　to　the　increase　in　the　prediction　accuracy　rate　of　the　window　being　opened　by　2.0%　and　3.3%　according　to　the　comparison　with　the　original　model　based　on　dummy　variables　and　the　common　model　based　on　continuous　variables,　respectively.　This　study　can　provide　a　reference　value　for　simulating　energy　consumption　in　office　buildings　in　the　future.　©　2023,　Tsinghua　University　Press.