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The paper presents an overview of the methods in the materials selection, offers some statistical heuristics in the decision process and a few ideas about a statistical approach for engineering applications, with some solved numerical examples. The complexity of the decisions in the present engineering problems imposes the use of new techniques, much more computer assisted, based on mathematics and psychology. A preliminary structuring of materials can be offered by cluster analysis: the agglomerative hierarchy gives a starting point in the classification practice. Further, a graphical selection method, based on eigenvalues and -vectors, was detailed and exemplified. Principal Component Analysis (PCA), a standard technique to reduce multivariate data sets to lower dimensions, was used in the selection of materials, with the possibility of simplification and implantation on a computer. The multiple-criteria decisionmaking (MCDM) or multiple-criteria decision analysis (MADM) , incorporating analytic hierarchy process (AHP), cover the high expansion of materials in the field of material classification.