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Cutting forces prediction is very important in micromilling for cutting tool's design and process planning. This paper presents a new model for uncertainty estimation of dynamic cutting forces in micromilling using a type-2 fuzzy rule-based system. The type-2 fuzzy estimation not only filters the noise and estimates the instantaneous cutting force in micromilling using observations acquired by sensors during cutting experiments, but also assesses the uncertainties associated with the prediction caused by the manufacturing errors and signal processing. Moreover, the interval output of the type-2 fuzzy system gives very useful information to machine tool controllers in order to maximize material removal while controlling tool wear or tool failure to maintain part quality specifications.