This study aimed to develop both the idiotype and the simulated idiotype form utilizing environment-adjusted data. The idiotype was derived from the adjusted data after removing environmental effects, whereas the simulated idiotype was generated from the same regression framework by applying controlled deviations to represent realistic improvement potential. In this study, the term “idiotype” represents the ideal genotypic pattern, while the simulated idiotype represents its optimized, biologically plausible form. The experiment was conducted as a split-plot arrangement within a randomized complete block design (RCBD) to test six organic and mineral fertilizer combinations in the main plots and six maize genotypes in subplots. The idiotype showed a high coefficient of determination (R²=0.9548), confirming that the developed pattern effectively represents the true genetic behavior of the studied genotypes. The simulated idiotype, on the other hand, exhibited a 16.18% increase in grain yield relative to the developed idiotype. Integration with stability indices, including the Eberhart and Russell parameters, Lin and Binns (Pi) and Wricke (Wi²), together with the GGE biplot showed that genotype G3 (5018) was found to be the most stable and high-yielding genotype, and environment E5 (320N+200P2O5+80K2O kg ha-1 + 4 tons ha-1 of organic fertilizer) was found to be the optimal environment combining high representativeness and discriminating ability. The results validate that the methodologies employed to derive both the idiotype and simulated idiotype, together with stability parameters and GGE biplot analysis, constitute a robust analytical framework for identifying stable, high-yielding maize genotypes across multiple environments, determining the most representative evaluation environment, and delineating idiotypes for breeding program enhancement.