Background. The current rate of production and consumption of meat poses a problem both to peoples' health and to the environment. This work aims to develop a simulation of peoples' meat consumption behaviour in Britain using agent-based modelling. Methods. The agents represent individual consumers. The key variables that characterise agents include sex, age, monthly income, perception of the living cost, and concerns about the impact of meat on the environment, health, and animal welfare. A process of social influence is modelled with respect to the agents' concerns. Influence spreadsis exercised across two eating networks (i.e. co-workers and household members) depending on the time of day, day of the week, and agents' employment status. Empirical dData from a representative sample of British consumers is used to empirically groundinform the model. Different experiments are run simulating interventions of application of social marketing campaigns and a rise in price of meat. The main outcome is the average weekly consumption of meat per consumer. A secondary outcome is the likelihood of eating meat. Analyses are run on the overall artificial population and by subgroups. Results. The model succeeds succeeded in reproducing observed consumption patterns. Different sizes of effect observed on consumption emerged depending on the application of a social marketing strategy approach or a price increase. Price increase has a greater effect than environmental and animal welfare campaigns, while a health campaign has a larger impact on consumers' behaviour than the other campaigns. An environmental campaign targeted at consumers concerned for environment backfired increasing the consumption in the population rather than reducing it. Conclusions. The results of the simulation experiments are mainly consistent with the literature on food consumption providing support for the future model of public strategies to reduce meat consumption