Genotype by environment interaction (G × E) influences crop ideotype selection and resilience to the growing environment conditions associated with climate change. Crop performances for economic traits have polygenic inheritance and subject to G × E, necessitating a detailed understanding of phenotypic plasticity, genetic variability, and associated impact on crop adaptation and tolerance to abiotic (e.g. drought, heat, and salinity) and biotic (e.g. insect pests and diseases) stresses. Robust statistical models and emerging molecular tools are crucial to dissect the magnitude and effects of G × E and guide genetic analysis and breeding of climate-smart crop cultivars for release and commercialization. Therefore, this chapter aims to provide an overview of the molecular basis of G × E and its associations in genotype selection for environmental adaptation. The review highlights the historical perspectives and an overview of G × E analysis and its applications. This is followed by the molecular basis of environmental adaptation for variable agro-ecologies; breeding for environmental resilience; integrated omics selection for adaptation, genetic modification of crops for stress adaptive traits, and participatory or demand-led plant breeding for local adaptation and marketplace. Further, the paper presents the challenges and future directions in integrating multi-environment data for G × E analysis, harnessing big data, AI, and machine learning to predict G × E effects and the future of breeding environmentally resilient crops. The review enables predictive modelling of G × E to guide crop genetics and breeding and release of demand-led and adaptive crop varieties.