Opening　windows　is　by　far　the　simplest　means　of　ventilation.　It　is　also　crucial　for　energy　efficiency　and　for　creating　a　comfortable　indoor　environment.　During　the　last　decade,　researchers　have　made　great　strides　in　investigating　occupants＇　window　operation　patterns.　However,　the　different　research　methods　used　to　capture,　recognize,　and　model　behavior　across　the　literature　make　it　difficult　to　compare　the　results　between　studies.　This　has　greatly　impeded　the　application　of　window　opening　behavior　models　to　build-ing　energy　performance　simulation　software.　Therefore,　this　paper　aims　to　provide　a　comprehensive　review　of　occupants＇　window　opening　behavior　in　relation　to　four　aspects.　The　first　aspect　is　data　collec-tion　methods,　whereby　different　data　collection　methods　are　analyzed,　and　the　limitations　of　the　existing　monitoring　devices　are　pointed　out.　The　second　aspect　is　the　factor　analysis,　whereby　the　main　correlated　factors　for　different　building　types　are　summarized.　In　particular,　it　is　assessed　whether　indoor　temper-ature　and　indoor　CO2　concentration　are　drivers　of　the　window　opening　behavior.　The　third　aspect　is　the　characterization　of　behavioral　diversity,　whereby　the　existing　methods　to　characterize　behavioral　diver-sity　are　classified　and　compared.　The　final　aspect　is　prediction　models,　whereby　the　adaptability　of　var-ious　prediction　models　and　the　mutual　validity　of　model　evaluation　indicators　are　discussed.　In　the　future,　scholars　will　need　to　make　efforts　to　expand　the　test　sample　size,　quantify　window　opening　angles,　consider　the　diversity　of　behavior　and　unify　model　evaluation　metrics.　This　would　help　the　appli-cation　of　predictive　models　in　supporting　building　design　and　the　evaluation　of　the　effectiveness　of　energy　efficiency　technologies.(c)　2022　Elsevier　B.V.　All　rights　reserved.