Dendrometers are vital tools for studying the response of trees to intra-annual environmental changes in different temporal resolutions, ranging from hourly, daily to weekly time resolution. Dendrometers are increasingly used in forest management and tree physiological studies. Besides the data analysis, data processing is also challenging, time-consuming and potentially error-prone due to the immense number of measurements generated by self-registering electronic dendrometers. We present the package 'dendRoAnalyst' based on R statistical software to process and analyse dendrometer data using various approaches. This package offers algorithms for handling and pre-cleaning of dendrometer data before the application of subsequent data analytical steps. This includes identifying and erasing artefacts in dendrometer datasets not related to actual stem circumference change, identifying data gaps within records, and the possibility of change(s) in temporal resolution. Furthermore, the package can calculate different daily statistics of dendrometer data, including the daily amplitude of tree growth. The package dendRoAnalyst is therefore intended to facilitate researchers with a collection of functions for handling and analysing dendrometer data.