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Applied a non-radical non-oriented Slack Based Measure (SBM) model of Data Envelopment Analysis (DEA) to measure the linkage efficiency between the two sectors from 2009 to 2016. The paper analyzes the current situation of manufacturing and logistics efficiency, presents a way to improve the linkage efficiency of manufacturing and logistics industry, and using Tobit regression to analyze the environmental factors that affect the linkage efficiency. The results show that: Totality, the two industries in the three northeast provinces show a steady development trend in the period from 2009 to 2016, but the development of the two industries in northeast China is still insufficient. Unexpected pollutant output is the main reason for the decline of manufacturing efficiency in the regions. The redundancy of input factors is the main reason that affects the efficiency decline of the logistics industry. The results of Tobit regression analysis show that the investment of science and technology and opening to the outside world have a positive influence on the efficiency of the two industries, and government consumption has a negative effect on the efficiency of the two industries. This is to correctly understand and grasp the status of two industry linkage development in three northeast provinces. And it provides a certain basis for the development policy of the two-industry linkage development. Implications: Due to the availability of data, reference to the relevant achievements of the research on the linkage between manufacturing industry and logistics industry. The transportation industry, warehousing, and postal and telecommunications industry data are generally used as logistics industry data. Manufacturing data replaced by industrial data. The manufacturing industry is the core industry in the industrial system. Its output value accounts for more than 90% of industrial output value, so it can reflect the development trend of the manufacturing industry in general. [ABSTRACT FROM AUTHOR]