Sepsis is a life-threatening organ dysfunction syndrome caused by a dysregulated host response to infection. Due to different infection sources, pathogens and basic conditions of patients, there is significant heterogeneity in clinical manifestations, response to treatment and prognosis of patients with sepsis. Accurate classification and individualized treatment of sepsis will help to further improve the prognosis of patients with sepsis. In recent years, the integration of artificial intelligence and bioinformatics has brought new opportunities for the research of sepsis classification. This review systematically introduces a variety of sepsis classification methods and their clinical application value. The clinical data in the electronic medical record, such as the dynamic changes of vital signs such as body temperature, can be used as the basis for sepsis classification. Different subtypes of body temperature trajectories have differences in physiological characteristics and prognosis, which contributes to predict the prognosis of patients and guide fluid management strategies. Biomarker classification can more comprehensively reflect the pathophysiological state of patients. Immune index classification is helpful to identify immunocompromised patients so as to carry out targeted immunotherapy. Transcriptome data and genotyping reveal the heterogeneity of sepsis at the molecular level and provide a new perspective for precision medicine. In addition, a detailed systematic review of sepsis-related organ function damage, such as acute respiratory distress syndrome (ARDS), acute kidney injury (AKI), and acute liver injury, has also been conducted, which is helpful to develop targeted organ protection and treatment strategies. These typing methods have shown good application prospects in clinical practice. However, there are still limitations in the current research, such as typing stability and biomarker selection, which need to be further explored. Future research should focus on the development of stable and efficient typing tools to achieve precise treatment of sepsis and improve the prognosis of patients.