The identification of stable genotypes across environments has gained significance in crops like guar, where yield instability or fluctuation has been seen regularly. The current review is a discussion on different stability models used in guar to determine stable genotypes, environment discrimination, and genotype by environment crossovers by conducting multi-location trials. Classical approaches such as Finlay–Wilkinson regression and Eberhart–Russell analysis evaluate linear responses to environmental indices, offering insights into adaptability and predictability. Multivariate techniques like AMMI and GGE biplot analysis integrate additive and multiplicative components to visualize genotype performance patterns and mega‑environment structures. Collectively, these models support breeders in selecting high‑yielding, widely adapted, and resilient cultivars, thereby strengthening crop improvement programs under increasing climatic variability especially in arid and semi-arid regions where crops like guar are generally cultivated.