China　has　made　remarkable　achievements　in　reducing　carbon　emissions　in　recent　years.　However,　there　is　still　much　reduction　room　before　achieving　carbon　neutrality.　In　Beijing,　the　capital　of　China,　it　is　a　strategic　choice　to　respond　to　global　climate　change　by　promoting　green　and　low-carbon　development.　This　paper　calculates　the　carbon　dioxide　emissions　of　key　industries　in　Beijing　and　analyzes　the　temporal　evolution　trend　of　carbon　emissions.　Carbon　dioxide　emissions　in　Beijing　before　2030　are　predicted　based　on　the　grey　prediction　GM　(1,1)　and　BP　neural　network　model.　The　effects　of　factors　of　carbon　dioxide　emissions　are　discussed　using　the　threshold　regression　model　under　different　economic　conditions.　The　results　show　that　energy　consumption　intensity,　GDP　per　capita,　and　the　ownership　of　civil　cars　have　a　positive　impact　on　carbon　dioxide　emissions,　while　the　number　of　permanent　residents　and　urban　green　space　areas　have　a　negative　impact　on　carbon　dioxide　emissions.　These　findings　of　carbon　emission　prediction　and　influencing　factors　contribute　to　carbon　reduction　path　design.　Related　policy　implications　on　carbon　emission　reduction　are　put　forward　from　the　aspects　of　promoting　industrial　upgrading,　accelerating　the　construction　of　advanced　economic　structures,　optimizing　transportation　structures,　and　strengthening　green　building　development.