Multi-trait-based selection has a great potential to increase genetic gain in plant breeding programs. In this study, the Smith-Hazel classic indices (SH1 and SH2), the modern ideotype-design index (FAI-BLUP) and the recently proposed multi-trait genotype-ideotype distance index (MGIDI) were compared and used to select superior wheat genotypes for 13 important agronomic traits with negative and positive desired gains. Thirty-four wheat genotypes were evaluated in a randomized complete blocks design with three replications under semi-arid rainfed environment of Eastern High Plateaus of Algeria. The selection differential for all traits was performed considering a selection intensity of 15%. The most efficient selection was obtained by MGIDI index, which outperformed the Smith-Hazel and FAI-BLUP indices with higher desired gains considering all traits simultaneously. The MGIDI provided negative gains (-2.20% ≤ gains ≤ -0.07%, a total of -4.71%) for all the three traits that wanted to decrease and positive gains (-0.41% ≤ gains ≤ +6.59%, a total of +14.32%) for eight of the ten traits that wanted to increase. Thus, MGIDI can greatly increase the efficiency of selection for multiple traits in wheat breeding programs.