A range of statistical tools is used in plant breeding to quantify genotype × environment interaction and to assess the stability of yield expression. These methods include regression-based models, nonparametric approaches, and multivariate techniques. Regression procedures are useful for describing the way a genotype responds to environmental change through the slope of its response curve and the magnitude of deviation from that trend. Nonparametric methods are particularly valuable when the assumptions required for classical parametric statistics, such as normality of distribution or homogeneity of variance, are not fully satisfied. At the same time, multivariate approaches offer a broader analytical perspective, because they are able to reveal complex interaction structures that cannot be adequately represented by a single statistic, especially when many test environments are included.