Advancing building energy efficiency represents a crucial pathway toward decarbonizing the construction industry. This study is based on the bibliometric method to analyse the quantitative analysis of academic literature related to building energy efficiency technology in China in web of science database from 2017 to 2024. By studying the publication trends, journal characteristics, number of article citations, research contributions from academic institutions, as well as the popular keywords of research and the future direction of theme evolution in this field, the study provides a reference value for researchers’ future research collaborations. The findings reveal that a rapid development in China’s building energy efficiency research, with CHEMICAL ENGINEERING JOURNAL emerging as one of the most influential journals in this field. The analysis identifies WANG Y, ZHANG Y, LIU Y, and WANG L as the most influential researchers in building energy efficiency technology. Institutionally, the Chinese Academy of Sciences lead in research output and impact. Emerging trends are reflected in the fastest growing keywords such as “energy efficiency”, “photocatalysis”, and “machine learning”. However, the application of advanced methodologies like “deep machine learning” is not yet common in China's building energy efficiency, highlighting a critical area for future exploration. This paper provides a comprehensive foundation for guiding collaborative efforts and deepening scholarly engagement in building energy efficiency technologies.