At　present,　the　main　focus　of　research　lies　in　examining　the　connection　between　economic　complexity　and　carbon　emissions　as　a　whole,　but　there　is　a　scarcity　of　quantitative　investigations　on　the　link　between　the　above　variables　within　specific　industries.　Therefore,　this　study　introduces　economic　complexity　as　a　new　variable　to　build　a　panel　model　within　the　traditional　Environmental　Kuznets　Curve　framework.　Based　on　the　data　of　the　countries　along　the　Belt　and　Road　from　1998　to　2018,　we　used　the　Granger　causality　test　to　examine　the　causal　relationship　between　variables,　and　use　the　Fully　Modified　Ordinary　Least　Square　and　Dynamic　Ordinary　Least　Square　methods　to　estimate　the　coefficients　of　variables.　The　key　factor　linking　economic　complexity　and　carbon　emissions　in　the　logistics　industry　is　technology　innovation　Economic　complexity　can　explain　and　predict　the　changes　in　carbon　emissions　of　logistics　industry　more　reasonably,　and　the　relationship　between　them　in　line　with　the　environmental　kuznets　curve　hypothesis.　Only　high-income　countries　can　increase　economic　complexity　while　reducing　carbon　emissions　of　logistics　industry.　Based　on　the　empirical　analysis,　it　is　suggested　that　upper-middle　income　and　lower　middle-income　countries　can　formulate　relevant　policies　and　regulations,　and　high-income　countries　can　improve　the　relevant　policies　and　regulations　to　promote　the　reduction　of　carbon　emissions　of　the　logistics　industry.　Studying　the　impact　of　economic　complexity　on　carbon　emissions　in　the　logistics　industry　can　help　better　predict　and　respond　to　the　impact　of　climate　change　on　the　logistics　industry.