<p>The role of demographic factors and disease in altering bone mineral density remains a topic of increasing importance for our aging population. As a technique for obtaining detailed insights into bone density, quantitative computed tomography, where detailed estimates of local bone density can be obtained from computed tomography scan data, has gained popularity in recent years. This approach is particularly useful for obtaining measurements opportunistically from clinical scans, however given the large amount of data generated, processing and drawing insights from the results can be challenging. This paper describes an open-source package, “BoneDensityMapping”, which is built in the R statistical computing environment and provides tools to process, analyze, visualize bone density data estimates derived from quantitative computed tomography. The package can be used to process scan data at the individual or group level. In this article, we cover the primary functions and workflows of the package, then demonstrate its utility on a dataset of scaphoid bones, showing a comparison between younger and older adults and identifying regions where there are notable differences. With the ability to regularly update the package with new functions, the package allows for continued improvement and advances to match the state of the science, as well as facilitating the sharing of code and analysis methods.</p>