Background:　To　analyze　the　causes　and　impact　mechanisms　of　the　severity　of　traffic　accidents　in　the　central　urban　area　of　Beijing,　this　study　focuses　on　1,348　traffic　accident　data　from　the　central　urban　area　of　Beijing　from　2013　to　2015,　analyzing　the　main　factors　influencing　the　severity　of　traffic　accidents　in　the　central　urban　area　of　Beijing.　Method:　Initially,　accidents　are　categorized　into　three　types:　property　damage　accidents,　injury　accidents,　and　fatal　accidents.　Eleven　factors　related　to　the　severity　of　accidents　are　selected,　and　tolerance　and　Variance　Inflation　Factor　(VIF)　tests　are　used　to　check　for　multicollinearity,　ensuring　that　there　are　no　multicollinearity　issues　among　the　chosen　variables.　Subsequently,　with　the　severity　of　accidents　as　the　dependent　variable　and　the　11　potential　influencing　factors　as　independent　variables,　an　ordinal　logistic　regression　model　(OLR)　is　constructed　to　comparatively　analyze　the　specific　impacts　of　each　factor　on　the　severity　of　traffic　accidents　in　the　central　urban　area　of　Beijing.　Result:　The　study　finds　that　collision　vehicle　type,　speeding,　non-physically　separated　roads,　cross-sectional　road　position,　and　holidays　are　the　main　factors　affecting　the　severity　of　traffic　accidents　in　the　central　urban　area　of　Beijing.　Conclusion:　The　findings　of　this　study　can　provide　references　for　urban　road　planning　or　the　formulation　of　traffic　safety　measures　in　the　central　urban　area　of　Beijing,　aimed　at　reducing　and　preventing　deaths　caused　by　road　traffic　accidents.　©　2024　Copyright　held　by　the　owner/author(s).