This chapter provides an overview of classification, a key method in data analysis. It explains different techniques for data classification using large language models (LLMs), including open-access models and detailed prompts for zero-shot, one-shot, and few-shot classifications. The chapter illustrates how LLMs can enhance qualitative analysis by leveraging their classification capabilities. Additionally, the chapter discusses the importance of prompt design and the cautious use of LLMs. This suggests techniques for improving reliability and the use of balanced approaches when selecting methods for specific research objectives.