The Martini model, a coarse-grained force field for biomolecular simulations, has been widely applied since its release a decade ago. Based on a building block principle, it combines speed and versatility while maintaining chemical specificity. This review covers the current state of the model, highlighting recent advancements and shortcomings, and discusses future developments. The Martini model is designed to provide a simple, computationally efficient, and flexible tool for simulating a broad range of biomolecular systems. It maps four heavy atoms plus associated hydrogens to a single interaction center, balancing computational efficiency and chemical representability. The model includes non-bonded interactions described by a Lennard-Jones potential and bonded interactions using standard potential energy functions. Validation of the Martini model has been conducted through comparisons with atomistic simulations and experimental data, demonstrating its accuracy in predicting partitioning behaviors and membrane properties. The model has been applied to various biomolecules, including lipids, peptides, proteins, sugars, polymers, nanoparticles, and dendrimers. Key applications include lipid membrane characterization, lipid polymorphism, membrane protein-lipid interactions, membrane protein oligomerization, self-assembly of soluble peptides and proteins, conformational changes in proteins, peptide-induced membrane permeabilization, drug and gene delivery systems, lipoprotein particles, membrane fusion, lipid monolayers, surfactant self-assembly, carbohydrates, polymers, and nanoparticles. Despite its strengths, the Martini model has limitations, particularly in modeling lipid-lined membrane pores and certain aspects of protein dynamics. Future work aims to address these limitations and expand the model's applicability.The Martini model, a coarse-grained force field for biomolecular simulations, has been widely applied since its release a decade ago. Based on a building block principle, it combines speed and versatility while maintaining chemical specificity. This review covers the current state of the model, highlighting recent advancements and shortcomings, and discusses future developments. The Martini model is designed to provide a simple, computationally efficient, and flexible tool for simulating a broad range of biomolecular systems. It maps four heavy atoms plus associated hydrogens to a single interaction center, balancing computational efficiency and chemical representability. The model includes non-bonded interactions described by a Lennard-Jones potential and bonded interactions using standard potential energy functions. Validation of the Martini model has been conducted through comparisons with atomistic simulations and experimental data, demonstrating its accuracy in predicting partitioning behaviors and membrane properties. The model has been applied to various biomolecules, including lipids, peptides, proteins, sugars, polymers, nanoparticles, and dendrimers. Key applications include lipid membrane characterization, lipid polymorphism, membrane protein-lipid interactions, membrane protein oligomerization, self-assembly of soluble peptides and proteins, conformational changes in proteins, peptide-induced membrane permeabilization, drug and gene delivery systems, lipoprotein particles, membrane fusion, lipid monolayers, surfactant self-assembly, carbohydrates, polymers, and nanoparticles. Despite its strengths, the Martini model has limitations, particularly in modeling lipid-lined membrane pores and certain aspects of protein dynamics. Future work aims to address these limitations and expand the model's applicability.