The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue as it significantly impacts crop productivity and global food security. Plants have evolved complex mechanisms to combat metal(loid) stress, and omics approaches— notably transcriptomics, proteomics, and metabolomics—have emerged as transformative tools to elucidate the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools support these omics approaches by facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores the multifaceted strategies that plants use to adapt to metal(loid) toxicity, the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species, the integration of omics data with artificial intelligence and high-throughput phenotyping, and the latest insights into stress adaptations and tolerance mechanisms. The review highlights the potential of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue as it significantly impacts crop productivity and global food security. Plants have evolved complex mechanisms to combat metal(loid) stress, and omics approaches— notably transcriptomics, proteomics, and metabolomics—have emerged as transformative tools to elucidate the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools support these omics approaches by facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores the multifaceted strategies that plants use to adapt to metal(loid) toxicity, the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species, the integration of omics data with artificial intelligence and high-throughput phenotyping, and the latest insights into stress adaptations and tolerance mechanisms. The review highlights the potential of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.