Eucalyptus globulus is an important forestry species for wood and pulp industry; however, its low cold resistance is a serious disadvantage. In this work, chemometric techniques were applied on the leaves' free amino acid content of different E. globulus genotypes in order to select cold tolerant genotypes. Pattern recognition methods based on regularized discriminant analysis (RDA) were used to classify the genotypes by cold resistance using samples' foliar damages as reference of cold resistance. Correlation between the amino acids content and cold resistance of genotypes was determined from a partial least squares (PLS) model. RDA models showed an excellent classification of genotypes (100% of correctly assigned genotypes in external validation), especially when RDA was reduced to quadratic discriminant analysis (QDA). Arg, Tyr and Ala, showed the highest correlations with the foliar damage in the PLS model and they could be responsible to improve cold resistance to the studied genotypes.