For estimating imprecise system, a incremental learning regularized least squares support vector fuzzy regression model is proposed. this model is applying the fuzzy sets principle and incremental learning method. as against the solutions of a complicated quadratic progamming problem in previous support vector fuzzy regression model, the proposed model reduces memory and calculates time because of utilizing the historical training results and equality contrainsts. numerical examples are given to demonstrate the effectiveness of the proposed model.