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Classification algorithms have found high levels of application in a range of domains. One of the most important classification algorithms that is currently in wide use Classification And Regression Trees (CART), which yields accurate and consistent results in most multiple domains. A significant failing of CART and other similar algorithms is their inability to handle imprecision. This inability to handle the Â¿grey areasÂ¿ makes these algorithms less applicable to a range of domains such as Medicine and Finance. A well-regarded method for handling such imprecision is Fuzzy Logic, and in this paper a novel algorithm that combines CART and Fuzzy Logic is presented. Following the description of the implementation the experimental results presented which have been achieved through the use of the proposed FuzzyCART algorithm demonstrate an increased level of classification accuracy for medical data when compared to classical CART.