Plant transpiration is the largest evaporative flux from most vegetated ecosystems, playing a dominant role in energy balance, water and element cycling, ecosystem services, and water security. Quantification of plant-level transpiration, e.g. sap flux, is essential to land managers and scientists. Thermal dissipation probes (TDP) are reliable and affordable tools for measuring sap flux, but difficulties in replicable data processing often serve as a barrier to their use and interpretation of data. AquaFlux is an R package designed to efficiently process and analyze TDP data. This program maximizes data collection by continually importing raw TDP values and alerting the user of any malfunctioning sensors. Data processing is expedited through a user-friendly graphical interface, predictive algorithms, and data recovery options. AquaFlux’s post-processing options address gapfilling, radial trends in sap flux across sapwood, and rescaling from points to whole stems. To ensure reproducibility and transparency, all data processing steps are automatically documented, highlighting the impact of user decisions. AquaFlux confirms to emerging best practices in data science and TDP data processing and analyses. Understanding spatiotemporal patterns of sap flux and how they relate to plant traits is essential for enhancing agricultural productivity, optimizing land management planning, ecological studies, and improving climate modeling. AquaFlux provides a robust tool to facilitate predictive understanding of plant transpiration.