This thesis constructs a database of Chinese industrial policies (IPs) spanning the periodfrom 2010 to 2023, with a focus on renewable energy and green industrial transformation. Drawing on over 370,000 official policy documents sourced from the PKULaw database, the study applies natural language processing (NLP) techniques to identify, classify, and quantify industrial policies. Descriptive analyses reveal several important patterns: (1) the majority of IPs are issued by subnational governments, especially at the municipal level; (2) there is significant spatial heterogeneity in policy issuance, with certain less- developed provinces displaying unexpectedly high policy intensity; and (3) solar and electric vehicle (EV)-related policies dominate the industrial landscape, particularly after 2015. The thesis also provides correlation and causal analyses linking the number of IPs to economic indicators and green innovations.