For the purpose of protein-DNA recognition analysis, amino acids are classified on the basis of protein-DNA contacts geometry and statistics. However, the methods of crisp classification do not allow describing the diversity of properties of amino acids. Amino acid residues have a variety of properties and can simultaneously belong to different classes. So, the classification of amino acids with different types of fuzzing was used. Voronoi–Delaunay tessellation was used to determine the spatial relationship between the amino acids of proteins and DNA nucleotides. Classification of amino acids was carried out on the statistics of contacts and the statistics of area of contact between amino acids and nucleotides. Classic hierarchical and nonhierarchical methods were used for crisp classification of amino acids with different types of distance measures. General variation approach was used for fuzzy classification of amino acids. Using the proposed mathematical model, it was shown that about 30% of all contacts between amino acids and nucleotides in protein-DNA complexes are not random. Crisp classification methods showed the existence of clustering invariants of amino acids. By fuzzy classification methods, it was shown that 6 classes are optimal for protein-DNA recognition task. The fuzzy classification of amino acids data is supposed to be used to construct the substitution matrix for DNA-binding protein sequences