PRC (Precision-Recall Curve) analysis is a crucial technique for evaluating the performance of classification models. It provides a comprehensive insight of how the model's precision and recall change across different decision points. By visualizing the precision-recall pairs, we can identify the optimal cutoff that balances these two metrics accor