We recently proposed a framework to evaluate the impact of reporting bias on the meta-analysis of a network of interventions, which we called ROB-MEN (Risk Of Bias due to Missing Evidence in Network meta-analysis). In this presentation we will show the ROB-MEN Shiny app which we developed to facilitate this risk of bias evaluation process. ROB-MEN first evaluates the risk of bias due to missing evidence for each pairwise comparison separately. This step considers possible bias due to the presence of studies with unavailable results and the potential for unpublished studies. The second step combines the overall judgements about the risk of bias in pairwise comparisons with the percentage contribution of direct comparisons on the network meta-analysis (NMA) estimates, the likelihood of small-study effects, and any bias from unobserved comparisons. Then, a level of “low risk”, “some concerns” or “high risk” of bias due to missing evidence is assigned to each estimate. The ROB-MEN Shiny app runs the required analysis, semi-automates some of the steps and built-in algorithm to assign the overall risk of bias level for the NMA estimates and produces the tool’s output tables. We will present how the ROB-MEN app works using an illustrative example from a published NMA. ROB-MEN is the first tool for assessing the risk of bias due to missing evidence in NMA and is also incorporated in the reporting bias domain of the CINeMA software for evaluating the confidence in the NMA results.