This paper presents a simulation-based decision support approach for artillery target engagement, focusing on the integration of stochastic modelling and reliability-based evaluation into fire planning. Traditional artillery methods rely on deterministic models and consumption norms, which provide limited insight into the variability of fire effectiveness. The proposed approach employs Monte Carlo simulation to model firing accuracy and munition effects, producing probabilistic distributions of target damage. These outputs are evaluated using reliability-based criteria, enabling comparison of firing methods in terms of effectiveness, probability of success, and ammunition consumption. Results demonstrate that optimized firing methods can achieve the required effect (≥30% target damage) with the desired reliability (84%) while significantly reducing ammunition expenditure and exposure time compared to traditional approaches. The study highlights the potential of simulation-based decision support to improve efficiency and decision-making in artillery fire planning.