The advancements in DNA sequencing technologies brought new perspectives to the crop improvement process right after the first human genome was read. Next-generation sequencing (NGS) techniques are characterised by a high-throughput and highly accurate process to obtain RNA and DNA sequencing data. The post-NGS era in plant breeding is marked by the employment of high-density molecular markers spread throughout the crop genome. Genomic Selection (GS) is a tool that predicts the genetic merit of individuals using all available information derived from molecular markers, and it was proposed before the NGS era. This prediction tool leverages the linkage disequilibrium between markers and quantitative-trait-locus (QTL), and it is being applied mainly for highly quantitative traits using single or multi-trait approaches. The power of GS in crop improvement is highlighted in this chapter by discussing the potential of this tool in impacting the breeder’s equation components, such as selection intensity (i), selection accuracy (r), genetic variance (σ), and the selection time length (L), aiming to increase the response to selection or genetic gains. In addition, GS can help breeders to improve their understanding of the genotype-by-environment (G × E) interactions observed in multi-environment trials for optimising the allocation of resources. At the end of the chapter, we discuss the integration of information obtained through NGS techniques with other data types (layers), enabling the so-called multi-omics approach to increase the efficiency of prediction models, enhancing the applicability of this tool in breeding strategies.