Human gut microbiota is closely related to human health and diseases, so that the modeling and analysis of its metagenomic data is of great significance for scientific research and social application in the field of disease prediction and diagnosis. In this paper, we comprehensively assessed the tools of human gut microbiome data analysis, the principles and processes of prediction algorithms, as well as some typical application cases from the perspective of big data analysis and machine learning. It aims to promote the development of analysis technology for gut microbiome and explore effective approaches for gut microbiome analysis combined with machine learning algorithms. Furthermore, it can also provide reference for the development of new diagnosis and treatment methods based on gut microbiome data.