In this study, we determine the mutation relation among 333 H5N1 hemagglutinins of influenza A viruses according to their amino acid and RNA codon sequences. Then, we calculate seven probabilistic numbers, which have been developed by us since 1999, for each amino acid in these hemagglutinins. With the seven numeric numbers as independents and the probability of occurrence of mutation at each hemagglutinin position as depend- ent, we use the logistic regression to model 967 missense point mutations from 333 hemagglutinins to get the population estimates. Thereafter, we predict the future mutation positions in H5N1 hemagglutinin. Finally, we use the translation probabilities between RNA codons and mutated amino acids to predict the would-be-mutated amino acids in H5N1 hemagglutinin.