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As one of the five approved religions in China, Protestantism has continually posed a special threat to the Communist Party due to its foreign roots and ties, conflicting ideology, and elements of collective action often associated with democratization. In light of the Party’s increasing repression and efforts to “sinicize” Protestant churches in China, I investigate how this restrictive environment has influenced the content of church sermons in state-approved churches. Using computational text analysis on sermon content from state-approved Protestant churches in China between 2009 to 2020, I analyze the pastors’ degree and composition of self-censorship in their receptiveness to changes in the political environment. Specifically, I apply supervised and unsupervised machine learning techniques to investigate the broad trends in sermon content over time as well as narrower trends surrounding significant political events and politically sensitive dates. By focusing on messages shared in state-approved churches, I shed light onto the complex positions in which these Party-registered pastors maneuver. This research also contributes to the broader discussion of civil rights and state-society relations in the context of a strong authoritarian state.