Texture of the polycrystall is one of the most important parameter characterizing the material. Many properties (mechanic, magnetic, electric) of the polycrystalline material depends not only on single crystal properties but also on distribution function of crystallographic orientations of grains in the sample, what is called texture. In some sense, the texture fulfill the weight factor roll for averaging properties of the material. Having texture function and tensor of single crystal properties it's easy to calculate tensor of any properties of the textured material. The opposite case is extremely hard and in general exists no one procedure to determine texture fulfilling requested sample properties for a given single crystal properties. Till now, the new textures are projected using observations and trials and errors method. The paper will present general concept, based on Genetic Algorithms method, of completely automatic procedure realizing this goal. First the basic concepts and terms commonly used in texture analysis will be explained. Next two classical problems (pole figures and orientation distribution function recalculations) will be presented using classical and genetic algorithm approaches. The various possibilities of individuals representations will be discussed. Finally a simple case of prediction of a texture realizing requested property anisotropy will be presented.

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