**Metaprop: A Stata Command for Meta-Analysis of Binomial Data** **Background:** Meta-analyses are essential for synthesizing evidence from multiple studies on clinical and epidemiological questions. Appropriate statistical software is needed to perform these analyses, particularly for binomial data. **Methods:** Metaprop is a Stata program designed to perform meta-analyses of proportions. It builds on the existing `metan` command, which is typically used for pooling effects but can also handle proportions. Metaprop includes specific procedures for binomial data, such as exact binomial and score test-based confidence intervals. It addresses issues with proportions close to the margins by using the binomial distribution or the Freeman-Tukey double arcsine transformation to stabilize variances. **Results:** Two meta-analyses were applied to demonstrate Metaprop's capabilities. The first analysis pooled the prevalence of HPV infection in women with ASC-US, resulting in a pooled prevalence of 43% (95% CI: 38%-48%). The second analysis pooled the cure rate after treatment for cervical precancer using cold coagulation, yielding a pooled percentage of 94% (95% CI: 86%-97%). **Conclusion:** Metaprop allows the inclusion of studies with proportions equal to 0% or 100%, ensuring that all studies are retained without excluding those with extreme proportions. It provides appropriate methods for handling proportions near the margins and ensures that confidence intervals are within admissible values, unlike the original publication where `metan` was used. **Keywords:** Meta-analysis, Stata, Binomial, Logistic-normal, Confidence intervals, Freeman-Tukey double arcsine transformation**Metaprop: A Stata Command for Meta-Analysis of Binomial Data** **Background:** Meta-analyses are essential for synthesizing evidence from multiple studies on clinical and epidemiological questions. Appropriate statistical software is needed to perform these analyses, particularly for binomial data. **Methods:** Metaprop is a Stata program designed to perform meta-analyses of proportions. It builds on the existing `metan` command, which is typically used for pooling effects but can also handle proportions. Metaprop includes specific procedures for binomial data, such as exact binomial and score test-based confidence intervals. It addresses issues with proportions close to the margins by using the binomial distribution or the Freeman-Tukey double arcsine transformation to stabilize variances. **Results:** Two meta-analyses were applied to demonstrate Metaprop's capabilities. The first analysis pooled the prevalence of HPV infection in women with ASC-US, resulting in a pooled prevalence of 43% (95% CI: 38%-48%). The second analysis pooled the cure rate after treatment for cervical precancer using cold coagulation, yielding a pooled percentage of 94% (95% CI: 86%-97%). **Conclusion:** Metaprop allows the inclusion of studies with proportions equal to 0% or 100%, ensuring that all studies are retained without excluding those with extreme proportions. It provides appropriate methods for handling proportions near the margins and ensures that confidence intervals are within admissible values, unlike the original publication where `metan` was used. **Keywords:** Meta-analysis, Stata, Binomial, Logistic-normal, Confidence intervals, Freeman-Tukey double arcsine transformation