The genomic selection advantage for Fusarium head blight is promising but failed for Septoria tritici blotch. Selection of new breeding parents based on predictions must be treated with caution. Genomic selection (GS) is an approach that uses whole-genome marker data to estimate breeding values of untested genotypes and holds the potential to improve the genetic gain in breeding programs by shortening the breeding cycle and increasing the selection intensity. However, reported realized gain from genomic selection is limited to few experiments. In this study, a training population of 1120 winter wheat lines derived from 14 bi-parental families was genotyped with genome-wide single nucleotide polymorphism markers and phenotyped for Fusarium head blight (FHB) and Septoria tritici blotch (STB) severity, plant height and heading date. We used weighted ridge regression best linear unbiased prediction to calculate genomic estimated breeding values (GEBVs) of 2500 genotypes. Based on GEBVs, we selected the most resistant individuals as well as a random sample and tested them in a multi-location field trial. We computed moderate coefficients of correlation between observed and predicted trait values for FHB severity, plant height and heading date and achieved a genomic selection advantage of 10.62 percentage points for FHB resistance compared to the randomly chosen subpopulation. Genomic selection failed for the improvement of STB resistance with a genomic selection advantage of only 2.14 percentage points. Our results also indicate that the selection of new breeding parents based on GEBVs must be treated with caution. Taken together, the implementation of GS for FHB resistance, plant height and heading date seems to be promising. For traits with very strong genotype × environment variance, like STB resistance, GS appears to be still challenging.