Background The proposed sequential and combinatorial algorithm, suggested as a standard tool for assessing, exploring, and reporting heterogeneity in the meta-analysis, is useful but time-consuming particularly when the number of included studies is large. Metaplot is a novel graphical approach that facilitates performing sensitivity analysis to distinguish the source of substantial heterogeneity across studies with ease and speed. Method Metaplot is a Stata module based on Stata's commands, known informally as "ado". Metaplot presents a two-way (x, y) plot in which the x-axis represents the study codes and the y-axis represents the values of I-2 statistics excluding one study at a time (n-1 studies). Metaplot also produces a table in the 'Results window' of the Stata software including details such as I-2 and chi(2) statistics and their P-values omitting one study in each turn. Results Metaplot allows rapid identification of studies that have a disproportionate impact on heterogeneity across studies, and communicates to what extent omission of that study may reduce the overall heterogeneity based on the I-2 and chi(2) statistics. Metaplot has no limitations regarding the number of studies or types of outcome data (binomial or continuous data). Conclusions Metaplot is a simple graphical approach that gives a quick and easy identification of the studies having substantial influences on overall heterogeneity at a glance.