This paper presents an analysis of the applications and benefits of TCPGraphix, a tool addressing the need for effective visualization within the domain of Test Case Prioritization (TCP). With an intuitive user interface, TCPGraphix offers an integrated and efficient approach to handle and derive insights from the vast quantity of data produced from TCP processes, specifically TCP processes using Machine Learning (ML). Moreover, it incorporates interactive capabilities, enabling users to navigate and comprehend TCP data easily using a blend of existing and new evaluation metrics. This paper provides a comprehensive overview of TCPGraphix’s design, core features, and applications. TCPGraphix effectively tackles critical data analysis hurdles and empowers researchers to extract valuable insights from expansive data sets and their results.