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A method is proposed for modeling and classification of White Matter fiber tracts in the brain. The presented scheme uses classification trees in conjunction with spatial representation of the individual fibers, in order to capture the characteristic behavior of fibers belonging to a specific anatomical structure. The method is characterized by high classification speed, under 3 seconds for all the fibers in a typical DTI of a brain. The model has the ability to represent complex geometric structures and has an intuitive interpretation. Encouraging results are demonstrated for tract classification on real data from ten different subjects.