With the increase in scale and complexity of software projects, a large number of bug reports are generated during the testing process, among which duplicate bug reports are widely present, reducing the efficiency of developers in fixing bugs. The prediction of duplicate bug report has become one of the popular research fields in recent years, and its efficiency and accuracy need to be improved. Therefore, this study puts forward a prediction method of duplicate bug reports based on semantic extension and continuous queries. Through the construction of a bug report index thesaurus based on the theme model, the semantic extension of query sequences is conducted. Then, the bug report retrieval algorithm based on the continuous query is adopted to narrow the index space and improve the prediction accuracy and efficiency. Experimental results show that compared with the traditional prediction method of duplicate bug reports, the proposed method reduces the index space of bug reports by more than 50%, improves the prediction effect by up to 33.6%, and shortens the retrieval time by 41%–73%.