There are many applications of particle technology in which solid mixtures consisting of particles having the same chemical, mineralogical and physical properties are used. The particles are then distinguishable only by shape. The particle shape significantly influences the technological behaviour of the mixture and the properties of the materials produced. Therefore, mathematical procedures are necessary in order to determine the composition of such a mixture according to the proportions of certain particle shape classes. These classes are the respective components of the mixture. In this work, various statistical methods were tested to classify the particles by shape analysis. A two-component mixture of quartz and muscovite was used as a reference material. The results obtained by different theoretical methods were compared with each other. Alternative methods such as histogram fit and the EM algorithm provided better results than the conventional method of discriminant analysis, as expected. Because the statistical behaviour of the components can be estimated only using reference samples, a statistical error of about 5-10% depending on the respective sample size was met. However, this is a satisfactory result. It turned out that it is possible to conclude exclusively on the basis of the particle shape distribution about the composition of a mixture. The methodical knowledge obtained can be used in industrial applications such as the ceramic industry, the production of paints and the bulk solids technology.