This work proposes a quality index based on a graph of distance relationships, the Gabriel Graph, to analyze the performance of classification models. The results have shown a consistent correlation between the quality index and the model's predictions, both at an individual and global level. These findings emphasize the importance of considering the data space to explain and optimize the performance of classification models.