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Abstract Lahars, or volcanic mudflows, are one of the most devastating natural, volcanic hazards. Deadly lahars, such as the one that occurred after the Nevado del Ruiz, Columbia eruption in 1985, in which at least 23,000 people tragically lost their lives, threaten the safety and well-being of humans, the economy, and the infrastructure of many of the communities living in the vicinity of volcanoes. Due to their complex flow behaviors, lahars remain a major challenge to those studying them. We present an analysis of several rain-triggered lahar events at Volcán Fuego in Guatemala using both seismic and infrasound monitoring to quantify both ground vibrations and low-frequency atmospheric sound waves associated with these mudflows. Geophysical data collected over this field campaign quantifies flow parameters such as velocities, stage and the frequency of these rain-triggered lahars. Time-lapse imagery of lahar flows is compared with filtered seismo-acoustic signal characteristics to ascertain stage predictions and relationship to stage fluxes. Using random forest regression models, we establish moderate correlations (correlation coefficient modes 0.48–0.53) with statistical significance (pvalue = 0.01–0.02) between signal energetics and respective stage. Compiling a catalog of rain-triggered lahar events in Volcán de Fuego’s drainages over a season permits a dataset amenable to statistical analysis. Our goal is the development of new-generation geophysical monitoring tools that will be capable of remote and real-time estimation of flow parameters.