To build up efficient strategies in plant breeding programs, it is requested a certain level of knowledge about the genotype–by-environments interaction (GEI) effects over the crop to be improved. One efficient way to gather this information is using linear mixed models using a parsimonious structure of GEI pattern such as factor analytic (FA) structure. In this work, we applied a multivariate analysis using the FA structure on a dataset composed of 11 cotton genotypes (Gossypium hirsutum) which were evaluated in seven environments in Mozambique, to identify stable and wide/specific adapted genotypes. Using the FA structure, it has been possible to select genotypes with specific and broad adaptability for the environmental network. The results indicated that FK37, Flash, BA525 and BA919 were the most productive genotypes, reaching the highest scores for first Factor. Nevertheless, the FK37 genotype presented Factor 2 close to zero classifying it as the most stable followed by Flash cultivar. The genotypes ISA205, QM301 and Albar SZ9314 were considered the less productive, although QM301 presented good stability. These findings suggest that the FK37 genotype might be recommended for Mozambique, since it had good yield and potential stability when compared to the most cultivated varieties, CA324 and Albar SZ9314.