Given the cost and complexity of conducting a clinical trial, and the uncertainty as to how patients may respond to an intervention, researchers often collect as much data as possible in order to describe the safety and efficacy of a novel treatment. Data visualization plays a key role to effectively summarize and communicate the results of these investigations. One graphical display of note is the forest plot, a figure that presents one or more confidence or credible intervals vertically to communicate either the findings of multiple endpoints or a single endpoint from multiple groups. In this presentation, we describe several applications of the forest plot in the context of clinical trials, including safety and quality screening, subgroup analysis, sensitivity analysis of a primary endpoint, and meta-analysis. While we present many of the aforementioned examples in a Frequentist context, we also discuss how forest plots can easily communicate the results of complex Bayesian models that utilize Markov Chain Monte Carlo (MCMC). We illustrate these examples using the freely available JMP forest plot add-in.