The three-dimensional conformation of a small molecule depends on the combination of bond lengths, bond angles, and torsional angles between all atoms connected by covalent bonds within the molecule. These properties are determined by the interactions within the molecule and between the molecule and the solvent. Small molecule conformation prediction plays a fundamental role in drug discovery, serving as a cornerstone for understanding molecular interactions, binding affinities, and biological activity. This computational process involves determining the three-dimensional structures that small molecules, such as potential drug candidates, can adopt in different environments. Since a molecule’s bioactivity is dictated by its ability to interact with specific biological targets, accurately predicting its conformation is essential for rational drug design. In the past 20 years, advanced prediction methods integrating quantum mechanics, molecular dynamics, and machine learning have substantially improved the accuracy of conformation generation, allowing for the exploration of complex molecular systems with high reliability. Expectedly, the role of AI methods in small molecule conformation prediction is being further revealed.