Plant breeders perform multi-environment yield trials to identify superior genotypes for a specific region and to partition the target region into different mega-environments. In this investigation, the GGE-biplot was used to evaluate 15 bread wheat advanced lines for yield performance across five locations of Sindh, Pakistan. The results of the combined analysis of variance revealed that the genotypes, locations, and their interaction significantly affected the grain yield. The polygon view of GGE-biplot indicated that G4, G6, G8, G9, G13, and G2 were the vertexed genotypes while three rays divided the five locations into two mega-environments. First mega-environment comprised of only one location E1 for which G6 and G4 were the winner genotypes. The second mega-environment consisted of four locations viz. E2, E3, E4, and E5 which contained G8 and G9 as the winner genotype. The ranking biplot designated G6 as an ideal genotype followed by G8 and G11. The least average yield across all the environments was observed in genotypes G13 and G2. Comparison biplot based on ideal genotypes ranked the other favorable genotypes as G4 > G11 > G8. The environment ranking biplot revealed that E2 was an ideal location since it had excellent power to discriminate all the genotypes based on of grain yield and was more appropriate to represent the overall environments. Among five test locations, the discrimination power of three locations E2, E4, and E5 was very similar in ranking the wheat genotypes as the environmental vectors of these locations overlapped another. Overall, the maximum average yield was recorded for G11 (5925.0 kg ha^-1) followed by G6 (5852.5 kg ha^-1) and G8 (5831.0 kg ha^-1). Taken together, the wheat advanced lines G6, G8, and G11 showed good yield potential to become the candidate wheat lines for cultivation in Sindh province, Pakistan.