Given　that　crude　oil　prices　are　influenced　by　the　complex　interplay　of　political,　economic,　and　social　events,　leading　to　rapid,　substantial,　and　unpredictable　fluctuations,　the　associated　risk　has　received　considerable　attention.　How　can　we　quantitatively　characterize　the　impact　of　these　sudden　events　and　accurately　measure　crude　oil　price　risk?　To　achieve　this　objective,　the　paper　introduces　the　Prophet　Quantile　Regression　(ProphetQR)　model.　This　model　not　only　analyzes　the　impact　of　sudden　events　on　crude　oil　prices　but　also　evaluates　the　effectiveness　of　strategies　implemented　to　control　these　fluctuations.　It　also　forecasts　the　future　distribution　of　crude　oil　prices　and　measures　both　the　potential　upside　and　downside　risks　associated　with　crude　oil　price　volatility.　By　employing　a　multi-step　ahead　rolling　forecasting　approach　and　the　proposed　Prophet-QR　model,　this　study　draws　several　empirical　conclusions.　First,　the　Prophet-QR　model　demonstrates　superior　accuracy　in　prediction.　Second,　sudden　events,　such　as　the　Iraq　war　and　the　Libyan　war,　have　a　profound　impact　on　crude　oil　prices,　causing　the　oil　price　at　risk　(OaR)　to　rise　sharply.　Third,　the　implementation　of　oil　price　intervention　measures,　such　as　production　cuts　and　strategic　reserve　releases,　is　highly　effective　in　mitigating　the　adverse　effects　of　sudden　events,　thereby　normalizing　the　OaR.　Continuously　monitoring　OaR　fluctuations　supports　informed　policymaking　and　effectively　reduces　the　adverse　impacts　of　sudden　events　on　future　crude　oil　prices.