This article is concerned with the reflectance spectra prediction based on a neural network developed for yarn from the roving reflectance spectra. The neural network developed is a multilayer feed-forward network. The first system is wavelength dependent, but its performance is not very satisfactory. The scaled conjugate gradient algorithm is incorporated into the backpropagation procedure to reduce the training phase. Once the wavelength independeuce of the transformation is established, a second system, whose performances agree with the experimental curves, is proposed. Finally, this system is completed by the introduction of a yarn parameter: the count. The results of this later model are quite promising.