To meet the growing demand for agricultural products, optimizing photosynthesis is a promising strategy to improve the crop yields. Phenotypic variance in photosynthesis has been observed within or between species. To further explore the potential of integrating photosynthesis parameters into crop breeding programs, we assessed agronomic traits and photosynthesis-related parameters across plant development in 631 barley recombinant inbred lines (RILs) from eight HvDRR sub-populations under field conditions. We found significant genotypic variations for the photosynthesis-related parameters and observed that their heritability ranged from 0.37 to 0.54. The observed multiple quantitative trait loci (QTL) and dynamic QTL for photosynthesis across different developmental stages underlined the complexity of the genetics of photosynthesis in barley. The considerably higher prediction ability of genomic prediction models than QTL based prediction models illustrates that the photosynthesis-related parameters are inherited in a more complex way than classical agronomic traits. However, our results impressively demonstrate that the prediction ability for yield can be increased by integrating photosynthesis-related parameters into genomic prediction models. Therewith, our results raised a novel perspective on increasing the efficiency of crop breeding programs by integrating photosynthesis-related parameters into prediction models.