A Harrell plot combines a forest plot of estimated treatment effects and uncertainty, a dot plot of raw data, and a box plot of the distribution of the raw data into a single plot. A Harrell plot encourages best practices such as exploration of the distribution of the data and focus on effect size and uncertainty, while discouraging bad practices such as ignoring distributions and focusing on $$p$$-values. Consequently, a Harrell plot should replace the bar plots and Cleveland dot plots that are currently ubiquitous in the literature.