Ground-based gamma-ray observatories rely on simulations of extensive air showers in the Earth’s atmosphere to calibrate their measurements. Modelling of air showers is, however, very difficult due to the large number of tracked particles, their possible interaction channels, and the effect of local atmospheric properties. Such a challenge can be tackled by utilizing Monte Carlo simulations which implement probabilistic models and statistical sampling to describe outcomes of very complex systems. This contribution will explore the process of simulating air showers in the CORSIKA 8 framework but will also explain the general features and approaches of Monte Carlo simulations to keep the discussion applicable beyond this particular use-case.