Opening　windows　is　an　important　factor　when　creating　a　comfortable　indoor　environment.　However,　research　on　window　opening　behavior　in　the　Chinese　region　of　hot　summers　and　cold　winters　is　limited.　In　addition,　almost　all　previous　research　in　this　area　has　focused　on　the　average　characteristics　of　the　sample　mostly　by　building　models　of　averageness,　which　largely　erases　individual　behavioral　attributes.　To　fill　the　gap,　an　empirical　measurement　and　modeling　study　of　window　opening　behavior　was　conducted　in　seven　households　in　Zigong,　Sichuan　Province.　The　following　was　found:　(1)　The　window　opening　behavior　of　residents　in　different　cities　in　hot　summer　and　cold　winter　regions　significantly　differed.　The　average　daily　duration　of　window　opening　by　the　test　subjects　in　this　paper　is　1122　min/day,　which　is　2-5.5　times　higher　than　previously　published　literature　on　this　climate　zone　suggests.　(2)　Among　the　test　subjects,　three　typical　window　opening　behaviors　were　noticed　based　on　the　average　daily　window-opening　probability　(R),　i.e.,　positive　(R＞95%),　negative　(R　＜　5%),　and　high　intensity　window　opening　(65%　＜　R　＜　95%).　The　first　two　categories　refer　to　personal　habits　of　residents　independent　of　environmental　and　temporal　factors.　(3)　High-intensity　window　opening　behavior　provided　imbalanced　data　which　is　more　accurately　modeled　by　the　random　forest　model　(98.9%　prediction　accuracy)　than　the　binary　logistic　regression　and　decision　tree　models,　i.e.,　14.5%　more　accurate　than　the　former　and　12.5%　more　accurate　than　the　latter.　Moreover,　it　was　found　that　the　relative　humidity　indoors　is　the　factor　that　contributed　the　most　to　the　accuracy　of　the　model.