 This paper examined various machine learning algorithms in order to identify the best model for detecting network intrusions. It found that decision trees using the CART algorithm achieved the highest macro F1 score of 0.96878 on a 28 class classification task. Additionally, this paper used XAI techniques to interpret the results and gain insight into the underlying causes of the observed patterns. This article was authored by Mantis Bassivisius and Aini Pulaski-Terrasivision.