OBJECTIVES: The caesarean section (CS) rate in Bangladesh surged by 42% in 2022 compared with the prior year. This study aimed to identify the main factors influencing CS decision-making in Bangladesh. DESIGN: Systematic review. DATA SOURCES: Global Health, PsycINFO, EMBASE, Medline and PubMed were systematically searched, and 308 studies were initially identified. ELIGIBILITY CRITERIA: Full-text original studies addressing the CS decision-making process in Bangladesh were included. There were no restrictions on study design and publication year. Non-English publications and studies conducted outside of Bangladesh were excluded. DATA EXTRACTION AND SYNTHESIS: Four qualitative and two mixed-methods studies met the full inclusion criteria. The included studies generated exclusively qualitative data; therefore, verbatim qualitative data were extracted and meta-synthesis was performed to identify themes. Finally, themes were mapped onto five levels of Bronfenbrenner's ecological systems theory (microsystem, mesosystem, exosystem, macrosystem and chronosystem). RESULTS: Across the studies, 158 participants were involved, including women, their family members and clinicians. The factors related to pregnant women (microsystem)-fear of childbirth; people (mesosystem)-family and community influences; clinicians and healthcare system (exosystem)-maternal preference, previous CS, fear of litigation, lack of accountability among obstetricians, lack of skills among nurses, lack of resources, absentee staff, disrespectful labour care, private agents activities; culture (macrosystem)-role of traditional birth attendants; time and life transition (chronosystem)-CS emerged as 'better'. CONCLUSIONS: The drivers for CS in Bangladesh are complex, and interventions to reduce overuse high rates will need to address more than 'health provider preference'. However, with only six relatively small studies identified, there is insufficient data to inform programmatic direction. In a country with 3 million births annually, there is a need for large-scale studies to quantify the main factors contributing to high CS rates in both the public and private sectors. PROSPERO REGISTRATION NUMBER: CRD42023490645.