Machine Learning and Deep Learning models are increasingly used in critical fields such as healthcare, finance, and cybersecurity, yet many operate as black boxes with limited visibility into how predictions are made. This lack of transparency can make it difficult for researchers, developers, and users to understand, validate, and trust model decisions, particularly when those decisions have significant consequences. There is a need for tools that make complex AI models more interpretable without compromising their performance. AlgoInsight addresses this gap by visualizing model decisions, analyzing feature contributions, and providing explanations that improve the transparency and reliability of AI systems.