Supersecondary structure code (SSSC), which is represented as a conformation term using the letters "H," "S," "T," and "D" for each amino acid peptide unit, can be utilized to look up supersecondary structure motifs like a helix-hairpin-helix (HhH) motif as character strings from the Protein Data Bank (PDB) structure files. The deep neural network-based conformational variability prediction system of protein structures (SSSCPreds) can simultaneously predict locations of protein flexibility or rigidity and the shapes of those regions with high accuracy. The sequence flexibility/rigidity map obtained from SSSCPreds has the prediction accuracy enough to discuss the correlation with the sequence-to-phenotype ones by mutations. In this chapter, the protocol of conformational variability prediction methods using SSSC, including the analysis of influenza virus hemagglutinins with amino acid mutations, is described. The conformational variability pattern of hemagglutinins for human influenza A H1N1pdm extremely resembles that of avian influenza A H5N1, except for the furin cleavage site of H5N1. The transition of virus variants is visually understandable from the maps, including the sharply increased flexibility with the insight into the recent unseasonal influenza epidemics in Japan. The prediction accuracy of conformational variability is low for proteins at pH 5 with very few measurement conditions, so this is the limitation of the conformational variability prediction method.