This paper deals with early and accurate breast cancer risk assessment for women. The use of texture analysis tools for the eventual development of an automatic system is proposed. In a first step, a standard procedure for obtaining x-ray mammograms is set up, the resulting radiographic images then being classified into four risk groups by a specialist. In a second step, specific and selected texture algorithms using both global and local statistical properties of the images are implemented. A number of x-ray mammograms have been studied. One of the resulting important observations is that it seems inappropriate to define a set of distinct classes of risk; rather, an increasing gravity degree correlated to a continuous evolution of the mammographic textures from the lowest to the highest degree of risk is to be preferred. Finally, a systematic comparison between the human classification and the numerical coefficients provided by the texture analysis is performed. The coefficients do not allow risk classification by themselves. A critical examination of these preliminary results leads us to a constructive discussion concerning the future developments of the proposed method.