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Whether green credit policy is conducive to improving the green innovation efficiency of heavy polluting industries is of great significance for China’s sustainable economic development and the construction of ecological civilization. This paper uses China’s Green Credit Guidelines to conduct a quasi-natural experiment based on relevant panel data of industries from 2007 to 2018. Specifically, it employs the Super-SBM model including non-expected output to measure the green innovation efficiency of 35 industries in China, and constructs the propensity score matching difference-in-difference model to explore how green credit policy impact on the green innovation efficiency of heavy polluting industries. The results show that the coefficient of difference-in-difference (DID\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${DID}$$\end{document}) was 0.262, which was significant at the 1% level; the coefficient of DID2012\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{DID}}_{2012}$$\end{document} was not significant; the coefficient of DID2013\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{DID}}_{2013}$$\end{document} was 0.490, which was significant at the 1% level; and the coefficient of DID2014\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{DID}}_{2014}$$\end{document} was 0.173, which was significant at the 1% level, indicating that green credit policy significantly contributes to the green innovation efficiency of heavy polluting industries, though with a lag effect. Further study finds that green credit policy pushes heavy polluting industries to improve green innovation efficiency by increasing financing cost and R&D investment; meanwhile, the heterogeneity test shows that the higher the state-owned share of the industry, the greater the positive effect of green credit policy on its green innovation efficiency. Finally, in order to accelerate the implementation of green credit policy and promote the green innovation efficiency of heavy polluting industries, banks can guide heavy polluting industrial enterprises through credit to carry out green technological transformation, heavy polluting industries should raise awareness of green innovation, and government should encourage heavy polluting industrial enterprises to carry out green innovation, and guide and supervise the state-owned enterprises in particular, so that they can improve cleanliness and achieve green economic development.