Due to their wide variety of properties, the representation of ice particles in cold and mixed-phase clouds are challenging to represent for microphysical schemes. To improve their representation, this study evaluates the implementation of predicted rime mass distribution in the bin microphysics scheme DESCAM. Based on the ‘fill-in’ concept, the model allows a smooth transition in ice particle properties between unrimed and graupel particles. Consequently, the terminal velocity and collision kernels of ice particles were updated as a function of rime fraction. These implementations are tested for a heavy snowfall event observed from March 7–9 during the ICE-POP 2018 field campaign in the mountainous Pyeongchang region of the Korean Peninsula. This event consists of a deep cloud triggered by a low-pressure system, followed by a shallower cloud system formed by orographic lifting of marine air. We found that the rime mass fraction at ground simulated by DESCAM evolves similarly to the rime index measured by the MASC instrument. Furthermore, during the shallow cloud phase, the predicted rime implementation leads to an increase in ice particle number concentration and a decrease in mean particle size (from 1.5 to 1.0 mm). The new version of DESCAM leads to significant changes in the spatial distribution of precipitation, with strong local variations exceeding 10 mm, resulting in an increase of 6.5 % in total precipitation amount. Accounting for predicted rime mass gives a better agreement between the model and the ground based observations of ICE-POP 2018.