In this paper, we are focusing on the use of agent-based approach to generate simulations of various scenarios for border crossing points and making technology acceptance predictions. This paper is related to the Horizon 2020 project METICOS¹¹https://meticos-project.eu/, for which we are extracting user (traveler and border control staff) perceptions from sources such as online social networks e.g., Twitter, Web, Interviews, Questionnaires etc. However, for the scope of this paper we have only included the synthetic data for the experiments to validate the proposed simulation model. The existing studies made a strong justification for choosing this approach to model the defined problem. To the best of our knowledge, this paper is a first research study focusing on defining how agent-based modeling and simulation can be used to model border crossing scenarios and predicting the acceptance of the border control technologies by explaining travelers' profile based on synthetic data, perceptions based on manual rules. This is important for stakeholders who take decisions related to what technologies to place at the border crossing points and what features such technologies should have to improve throughputs and traveler and border staff satisfaction.