Several reviews have been conducted to assess the association between greenspace and overweight or obesity, but the conclusions were inconsistent. However, an updated comprehensive review and meta-analysis is warranted, because several high-quality papers have been published more recently. The objectives of this study are to systematically and quantitatively assess the evidence for a link between greenspace with overweight/obesity and to make specific recommendations for further research. We searched three English language databases, four Chinese language databases and the reference lists of previously published reviews for epidemiological studies on greenspace and overweight/obesity published before January 2020. We developed inclusion criteria, screened the literature and extracted key data from selected papers. We assessed methodological quality and risk of bias, and we graded the credibility of the pooled evidence. We also performed sensitivity analyses. Fifty-seven records met our inclusion criteria and were included in the study. Most studies were cross-sectional designs (81%) and were from developed nations (88%). More than half (55%) of the included studies found beneficial associations between greenspace and overweight/obesity in overall or subpopulations. Our meta-analytical results showed that greater normalized difference vegetation index was associated with lower odds of overweight/obesity in a statistically significant fashion (odds ratio [OR]: 0.88; 95% CI: 0.84, 0.91) but not residential proximity to greenspace (OR: 0.99; 95% CI: 0.99, 1.00), proportion of greenspace (OR: 0.96; 95% CI: 0.85, 1.08) or number of parks in an area (OR: 0.99; 95% CI: 0.97, 1.01). However, we detected high between-study heterogeneity in two of the four meta-analyses, which reduced the credibility of the pooled evidence. Current evidence indicates that there might be an association between greater access to greenspace and lower odds of overweight/obesity. However, additional high-quality studies are needed to more definitively assess the evidence for a causal association.