Integrating yield and stability of genotypes tested in unpredictable environments is a common breeding objective. The main goals of this research were to identify superior durum wheat genotypes for the rainfed areas of Iran and to determine the existence of different mega-environments in the growing areas of Iran by testing 20 genotypes in 4 locations for 3 years via GGE (genotype + genotype-by-environment) biplot analysis. Stability of performance was assessed by the Kang’s yield-stability statistic (YSi) and 2 new methods of yield-regression statistic (Ybi) and yield-distance statistic (Ydi).The combined analysis of variance showed that environments were the most important source of yield variability, and accounted for 76% of total variation. The magnitude of the GE interaction was ~10 times the magnitude of the G effect. The GGE biplot suggested the existence of 2 durum wheat mega-environments in Iran. The first mega-environment consisted of environments corresponding to ‘cold’ locations (Maragheh and Shirvan) and a moderately cold location (Kermanshah), where ‘Sardari’ was the best adapted cultivar; the second mega-environment comprised ‘warm’ environments, including the Ilam and Kermanshah locations, where the recommended breeding lines G16 (Gcn//Stj/Mrb3), G17 (Ch1/Brach//Mra-i), and G18 (Lgt3/4/Bcr/3/Ch1//Gta/Stk) produced the highest yields. Ranking of genotypes based on GGE was found to be highly correlated with that based on the statistics YSi and Ybi. The discriminating power v. the representative view of the GGE biplot identified Kermanshah as the location with the least discriminating ability but greater representation, suggesting the possible of testing genotypes adapted to both warm and cold locations at the Kermanshah site. The results verified that the statistics YSi and Ybi were highly correlated (r = 0.94**) and could be a good alternative for GGE biplot analysis for selecting superior genotypes with high-yielding and stable performance.