While two-rowed barley is usually preferred for malting and beer-making, six-rowed malting barley varieties appeared in Europe around 30 years ago, and several breeders have dedicated improvement programs on this specific germplasm. In this study, we evaluated the feasibility of genomic prediction for yield and malting related traits using 679 breeding lines from two French barley breeders, as well as a set of recently registered varieties. These lines were evaluated in five locations and two harvest years in an unbalanced design. Although the germplasm from the two breeders does show some trend towards differentiation, globally the whole panel did not show a clear-cut genetic structure. Predictive ability of GBLUP was evaluated through random cross-validation within and across breeder sets, and using cross-prediction between breeder sets. Results show moderate to high predictive ability (PA), particularly for malt friability and β-glucan content, for which predictive ability of 0.8 was obtained with training populations as small as 105 registered varieties and across breeding sets. The long range of useful linkage disequilibrium in this particular germplasm allows using as few as 2000 to 5000 markers to obtain high PA. Other prediction methods such as Bayesian LASSO, Bayes Cpi or EGBLUP did not improve predictive ability. These results are very encouraging for implementing genomic prediction of malting quality traits in applied breeding programs.