Ensuring food security amidst population growth and climate change while reducing dependence on unsustainable agrochemicals are dual challenge currently faced by global agriculture. Crop microbiome or microbial communities associated with crops play a vital role in increasing soil fertility, mitigating stresses and enhancing crop productivity. Limitations of traditional culture-based methods are circumvented by advances in molecular biology and thus enabling omics-based technologies such as metagenomics, metatranscriptomics, metaproteomics, and metabolomics to revolutionize our ability to study plant-associated microbiomes which allow for a comprehensive analysis of microbial community structure, active gene expression, protein functionality, and metabolic interactions within agricultural ecosystems. The chapter outlines optimal survey and sampling strategies, extraction methods of molecular resources of different types of meta-omics approaches, and bioinformatic pipelines essential for handling large and complex datasets. Sample heterogeneity, extraction biases, data integration, and the scarcity of reference databases are recognized as challenges. In order to produce stress-resilient crops through bioformulations and sustainable farming methods, it is crucial to integrate multi-omics methodologies for understanding of microbial interactions in a system mode. The promise of artificial intelligence (AI)-powered analytics, real-time sequencing, and synthetic microbial communities in microbiome engineering for sustainable agriculture is highlighted as perspective of use of meta-omics for crop improvement.