In this study, an analysis on the breaking elongation mechanism of the polyester/viscose blended open-end rotor spun yarns has been carried out. In addition, a back propagation multi layer perceptron (MLP) network and a mixture process crossed regression model with two mixture components (polyester and viscose blend ratios) and two process variables (yarn count and rotor speed) are developed to predict the breaking elongation of polyester/viscose blended open-end rotor spun yarns. Seven different blend ratios of polyester/viscose slivers are produced and these slivers are manufactured with four different rotor speed and four different yarn counts in rotor spinning machine. In conclusion, ANN and statistical model both have given satisfactory predictions; however, the predictions of ANN gave relatively more reliable results than those of statistical models. Since the prediction capacity of statistical models is also obtained as satisfactory, it can also be used for breaking elongation (%) prediction of yarns because of its simplicity and non-complex structure. In addition, it is also found in this study that yarn count, rotor speed and breaking elongation of polyester-viscose fibers and the blend ratios of these fibers in the yarn have major effects on yarn breaking elongation.