In Bolivia, the productivity of forage oat is rel-atively low. To address this issue, the present study aimed to identify more productive and stable genotypes using statistical methods such as GGE Biplot and BLUP (Best Linear Unbi-ased Prediction). The research was conducted in three different environments in Bolivia, eval-uating six commercial varieties of forage oats, including three from Instituto Nacional de In-novación Agraria (INIA-Peru) and the remaining from Centro de Investigación Forra-jera (CIF) -Violeta Bolivia. The data obtained were analyzed using GGE Biplot and BLUP, re-sulting in an average yield of 10.29 ± 3.51 t ha-1 of dry matter. BLUP exhibited a higher cumu-lative variance than GGE Biplot in the first two components. Both models demonstrated similar trends in terms of productivity and stability val-ues, facilitating the selection process. Consequently, Tayco and Texas were identified as the most promising genotypes due to their exceptional dry matter yield and phenotypic stability.