Delving into the intricate world of microbiomes through metagenomic analysis opens a window to understand the hidden interactions of microbial communities within diverse ecosystems. This chapter dissects the core aspects of metagenome analysis using R packages, emphasizing the need for adapting workflows to specific research questions and varied data types. The R-based analysis of microbiome data encompasses data import, meticulous preprocessing, insightful visualization, and powerful statistical interrogation, including differential abundance analyses. These analyses on predicted microbiota unlock invaluable insights into microbial responses, regulatory networks, and molecular signatures under specific biological or experimental conditions. The study of metagenomes through R has revolutionized our understanding of microbial communities and their vital roles in human health, agriculture, and environmental sustainability. This work serves as a roadmap for researchers navigating metagenomic data, with code snippets acting as a springboard for implementing data analysis steps within the R environment.