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Typically regression trees are not capable of generating a continuous output as a function of inputs and are not suitable for modeling process control problems. Fuzzy logic controllers offer an alternative approach to modeling such process efficiently but often rely on human experts to articulate a set of rules. The generation of fuzzy rules by experts is difficult and based on the subjective perception of individuals. This paper presents a novel approach to modeling process control applications using fuzzy regression trees. Two sets of experiments were designed and conducted. The first involved measuring the output gradient of the fuzzy regression tree to investigate the applicability of fuzzy regression trees in modelling process control applications. The second assessed the efficiency of the fuzzy model produced. The results have shown that an effective fuzzy model can be produced and as a consequence a considerable improvement in the performance can be achieved.