This paper reports on a case study - conducted within the European FP7 project "4FUN" - focusing on exposure of pre-school children to lead resulting from past emissions by non-ferrous smelters in Belgium (Northern Campine area). Exposure scenarios were constructed and simulated with the MERLIN-Expo tool to estimate external Pb exposure as well as the Pb body burden in children living in the vicinity of the former industrial sites as compared to children living in adjacent areas and a reference area. Simulations were run for several scenarios ranging from very simple to rather complex in order to study the effect of different simulation approaches (e.g., deterministic vs. probabilistic, individual vs. aggregated population exposure) and different exposure scenarios (e.g., with vs. without considering local food consumption or time activity patterns) on the model outcomes (predicted concentrations of Pb in environmental and human matrices). This paper discusses the two most complex scenarios, namely exposure at the aggregated population level and at the individual level for a random sub-sample of subjects, respectively. In the final and most realistic exposure scenario, simulating individual lead exposure, model predictions were shown to be higher than the biomonitoring data. Blood Pb levels in children, irrespective of the area they lived in, were overpredicted by MERLIN-Expo with a factor of about 2 on average. The model predictions for individual children overlap with the prediction interval calculated by MERLIN-Expo based on population averages, demonstrating the use of probabilistic approaches in risk assessment. While these results constitute a first verification of the model performance of MERLIN-Expo dealing with inorganic pollutants in a complex real-world exposure scenario and a demonstration of the robustness of the modelling tool, further validation and benchmarking efforts are required for a larger number of inorganic pollutants and different exposure settings.