Abstract: Some studies use advanced Large Language Model(LLM) technologies to understand legal facts and predict the defendant's charges,prison term and other judgment results.For further in-depth research,this paper chooses the more complex task of predicting legal judgments for multiple defendants,which is more challenging than predicting for a single defendant.Specifically,upgrading the interaction with LLM from a single-turn to multi-turn process to enhance LLM's understanding of criminal cases.In addition, two types of crime Knowledge Graphs(KGs) are construted to describe the case.The criminal relationship knowledge graph depicts the relationships of assistance between the defendants,while the sentencing circumstance knowledge graph represents the core criminal details of the case.Through crime knowledge graphs,a retrieval system is designed to provide LLM with references for similar case judgments.In experiments on predicting legal judgments for multiple defendants, the prediction results of the proposed method are better than the comparison methods,which shows that the designs of multi-turn LLM interactions and crime knowledge graphs are effective.

Key words: Multi-defendant, Legal judgment prediction, Large language model, Criminal knowledge graph