In this paper two areas of soft computing (fuzzy modeling and artificial neural networks) are discussed. Based on the fundamental mathematical similarity of fuzzy technique and radial basis function networks a new training algorithm for fuzzy models was introduced. A feed forward neural network (NN), a radial basis function network (RBF) and a trained fuzzy algorithm are compared for regional yield estimation of agricultural crops (winter rye, winter barley). As training pattern a data set from a training region (Maerkisch-Oderland district, Germany) and as test pattern a data set from a three times larger region were used. Specific advantages and disadvantages of these methods for the estimation of yield were discussed. Key words: Fuzzy modeling; artificial neural network; feed forward network; radial basis function network; training algorithm; yield estimation; agricultural crops