The main aim of the present study was to predict the most important yarn quality characteristics derived from cotton fiber properties that were measured by means of an HVI system. With this aim 15 different cotton blends were selected from different spinning mills in Turkey. The cotton fibers were processed in the short staple spinning line at Ege University Textile and Apparel Research-Application Center and were spun into ring yarns (20s, 25s, 30s and 35s). Each count was spun at three different coefficients of twist (alpha(e) 3.8, alpha(e) 4.2 and alpha(e) 4.6). Linear multiple regression methods were used for the estimation of yarn quality characteristics. Yarn count, twist and roving properties all had considerable effects on the yarn properties and therefore these parameters were also selected as predictors. After the goodness of fit statistics very large R 2 (coefficient of multiple determination) and adjusted R 2 values were observed. Furthermore, analysis of variance tables showed that our equations were significant at the alpha = 0.01 significance level.