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Cloud microphysics is a critical aspect of the Earth's climate system, which involves processes at the nano‐ and micrometer scales of droplets and ice particles. In climate modeling, cloud microphysics is commonly represented by bulk models, which contain simplified process rates that require calibration. This study presents a framework for calibrating warm‐rain bulk schemes using high‐fidelity super‐droplet simulations that provide a more accurate and physically based representation of cloud and precipitation processes. The calibration framework employs ensemble Kalman methods including Ensemble Kalman Inversion and Unscented Kalman Inversion to calibrate bulk microphysics schemes with probabilistic super‐droplet simulations. We demonstrate the framework's effectiveness by calibrating a single‐moment bulk scheme, resulting in a reduction of data‐model mismatch by more than 75% compared to the model with initial parameters. Thus, this study demonstrates a powerful tool for enhancing the accuracy of bulk microphysics schemes in atmospheric models and improving climate modeling. Plain Language Summary: Cloud microphysics is a complex set of processes that determine the formation and evolution of particles in clouds, which affects the Earth's climate by regulating precipitation and cloud cover. However, the vast difference in scale between the microphysics and large‐scale atmospheric flows makes it impossible to simulate these processes in climate models directly. Instead, climate models use simplified methods to represent cloud microphysics, which can result in inaccuracies. In this study, we focus on calibrating the simplified models with more detailed simulations of cloud microphysics using the super‐droplet method. We demonstrate a framework for calibrating the simplified models using high‐fidelity simulations, which improves the accuracy of these models. Key Points: A calibration framework for warm‐rain bulk microphysics parameterizations is presentedThe framework relies on a library of super‐droplet simulations of a rain shaftCalibrating a single‐moment microphysics scheme with the calibration framework substantially reduces the model‐data mismatch [ABSTRACT FROM AUTHOR]