How　to　effectively　aggregate　time-series　information　has　long　been　a　significant　issue　in　the　field　of　decision-making　method　and　decision　support　system.　This　paper　studies　a　dynamic　normal　distribution　stochastic　decision-making　method　that　is　based　on　the　time　degree　and　vertical　projection　distance.　A　dynamic　normal　distribution　number　weighted　arithmetic　average　(DNDNWAA)　operator　is　introduced,　and　a　time　sequence　weight　calculation　model　is　constructed　that　fully　considers　the　subjective　preference　of　the　historical　information　of　the　decision-maker.　An　attribute　weight-determining　model　based　on　vertical　projection　distance　is　presented　against　the　characteristics　of　normally　distributed　stochastic　variables.　The　original　dynamic　normal　distribution　stochastic　decision-making　information　is　aggregated　via　the　aggregation　operator　under　the　normally　distributed　stochastic　variables.　The　aggregated　comprehensive　stochastic　decision-making　information　based　on　stochastic　probability　distribution　theory　is　converted　into　interval　numbers,　and　the　interval　number　possibility　degree　model　is　applied　to　provide　a　solution　ordering　result.　Finally,　the　validity　and　rationality　of　the　method　proposed　in　this　paper　are　verified　by　analyzing　numerical　examples.　The　proposed　method　can　guide　decision-makers　to　make　better　decisions　in　dynamic　random　information　environment.