The reduction of childhood obesity through the promotion of a healthy lifestyle is one of the most important public health challenges at the moment. It is known that the unhealthy habits of children can cause unavoidable side effects in their early stage of life, including both physical and mental consequences. This work considers that the physical activity level of children is a behaviour that can be spread throughout the social relations of children in their daily life at school. Therefore, the aim of this work is to define what the best strategy is to find 'targets' (i.e., influential children that can initiate behavioural change) for physical activity (PA) interventions that would affect the average PA of a population of Dutch school classes. We tuned a model based on the influence of the children's peers in their social network, based on the data set from the MyMovez project-Phase I. Five intervention strategies were implemented, and their efficacy was compared. Once the targets were chosen, an increase of 17% was applied to their initial PA. Then, the diffusion model was run to verify the improvement on the PA of the whole network after one year. We discuss implications of the simulation results on which strategies may be used to make informed choices about the setup of social network interventions and future model improvements. Our results show that targeting more vulnerable children (i.e. in a worse environment) and applying a network optimization algorithm are the best solutions for this data set indicating that future interventions should aim for these two strategies.