OBJECTIVES: We synthesise evidence on sexual harassment from studies in low-income and middle-income countries (LMICs) to estimate its prevalence and conduct a meta-analysis of the association between sexual harassment and depressive symptoms. METHODS: We searched eight databases. We included peer-reviewed studies published in English from 1990 until April 2020 if they measured sexual harassment prevalence in LMICs, included female or male participants aged 14 and over and conceptualised sexual harassment as an independent or dependant variable. We appraised the quality of evidence, used a narrative syntheses approach to synthesise data and conducted a random effects meta-analysis. RESULTS: From 49 included studies, 38 focused on workplaces and educational institutions and 11 on public places. Many studies used an unclear definition of sexual harassment and did not deploy a validated measurement tool. Studies either used a direct question or a series of behavioural questions to elicit information on acts considered offensive or defined as sexual harassment. Prevalence was higher in educational institutions than in workplaces although there was high heterogeneity in prevalence estimates across studies with no international comparability. This posed a challenge for calculating an overall estimate or measuring a range. Our meta-analysis showed some evidence of an association between sexual harassment and depressive symptoms (OR: 1.75; 95% CI: 1.11 to 2.76; p=0.016) although there were only three studies with a high risk of bias. CONCLUSION: To our knowledge, this is the first systematic review to assess measurement approaches and estimate the prevalence of sexual harassment across settings in LMICs. We also contribute a pooled estimate of the association between sexual harassment and depressive symptoms in LMICs. There is limited definitional clarity, and rigorously designed prevalence studies that use validated measures for sexual harassment in LMICs. Improved measurement will enable us to obtain more accurate prevalence estimates across different settings to design effective interventions and policies.