Rockfall events are influenced by various climatic factors. Identifying these factors is crucial for anticipating rockfall events and managing the risks to infrastructure and populations. Previous studies have particularly highlighted rainfall and freezing conditions as key triggers, based on rockfall catalogs derived from visual observations or diachronic comparisons, with temporal precision ranging from a few to several days.</p> <p>The purpose of this study is to use a catalog derived from seismic detection, giving a much greater temporal accuracy, to explore and better understand the meteorological conditions that contribute to rockfall at Mont Saint-Eynard, a limestone cliff in the French Alps. This study introduces a probabilistic approach that combines different temporal horizons and cumulative models capturing delayed effects to analyze the influence of rainfall and freezing conditions on rockfall triggering. By integrating multiple statistical metrics relative to a specific condition including empirical probabilities, lift measures, confidence intervals and Chi-squared tests, we identified not only the likelihood but also the strength and reliability of triggering patterns. We identified the significant role of short term triggers like recent intense rainfall on high magnitude rockfall, and delayed effect of freezing depth in rockfall activity. This knowledge could be used to implement a risk management strategy.