Background: Despite the rapid spread of extended-spectrum beta-lactamase (ESBL) producing-Enterobacterales (ESBL-E) and carbapenemase-producing Enterobacterales (CPE), little is known about the extent of their prevalence in the Greater Mekong Subregion (GMS). In this systematic review, we aimed to determine the epidemiology of ESBL-E and CPE in clinically significant Enterobacterales: Escherichia coli and Klebsiella pneumoniae from the GMS (comprising of Cambodia, Laos, Myanmar, Thailand, Vietnam and Yunnan province and Guangxi Zhuang region of China). Methods: Following a list of search terms adapted to subject headings, we systematically searched databases: Medline, EMBASE, Scopus and Web of Science for articles published on and before October 20th, 2020. The search string consisted of the bacterial names, methods involved in detecting drug-resistance phenotype and genotype, GMS countries, and ESBL and carbapenemase detection as the outcomes. Meta-analyses of the association between the isolation of ESBL from human clinical and non-clinical specimens were performed using the "METAN" function in STATA 14. Results: One hundred and thirty-nine studies were included from a total of 1,513 identified studies. Despite the heterogeneity in study methods, analyzing the prevalence proportions on log-linear model scale for ESBL producing-E. coli showed a trend that increased by 13.2% (95%CI: 6.1-20.2) in clinical blood specimens, 8.1% (95%CI: 1.7-14.4) in all clinical specimens and 17.7% (95%CI: 4.9-30.4) increase in carriage specimens. Under the log-linear model assumption, no significant trend over time was found for ESBL producing K. pneumoniae and ESBL-E specimens. CPE was reported in clinical studies and carriage studies past 2010, however a trend could not be determined because of the small dataset. Twelve studies were included in the meta-analysis of risk factors associated with isolation of ESBL. Recent antibiotic exposure was the most studied variable and showed a significant positive association with ESBL-E isolation (pooled OR: 2.9, 95%CI: 2.3-3.8) followed by chronic kidney disease (pooled OR: 4.7, 95%CI: 1.8-11.9), and other co-morbidities (pooled OR: 1.6, 95%CI: 1.2-2.9). Conclusion: Data from GMS is heterogeneous with significant data-gaps, especially in community settings from Laos, Myanmar, Cambodia and Yunnan and Guangxi provinces of China. Collaborative work standardizing the methodology of studies will aid in better monitoring, surveillance and evaluation of interventions across the GMS.