Fast-growing companies stimulate innovation in different regions, as they use emerging technologies capable of developing new business models. Developed countries, as well as emerging countries, have actively adopted policies that encourage fast-growing companies as a way of contributing to economic development. Many of these organizations seek to expand their businesses internationally. International expansion offers organizations valuable opportunities for growth. International expansion strategies are influenced by factors such as personality traits and perceptions of CEOs and founders. The study seeks to answer the following question: “What are the factors that influence changes in the strategic choices of international expansion of fast-growing organizations, considering the managers' perception of the company's location, the manager's gender, and the number of employees what does this generate?” The main objective of the research is to analyse the factors that influence changes in the choices of the international expansion strategy of fast-growing organizations, considering the perception of managers both in relation to the location, their gender, and the number of employees, using the Bayesian Networks method. To achieve the general objective, the following specific objectives are required: Identify the factors that influence changes in the choices of the international expansion strategy of fast-growing organizations, according to the region evaluated, using the Bayesian Networks method; Analyse the factors that influence the decision-making process regarding the international expansion strategy of fast-growing organizations, considering the perception of managers based on their gender, using the Bayesian Networks method; and Examine the influencing factors that impact decision-making in the international expansion of fast-growing companies, considering the perspective of managers, according to the number of the team, through the application of the Bayesian Networks method. The research sample consisted of fast-growing companies located in Amsterdam, Berlin, London, New York, and Paris. The Bayesian Networks method was used in the analyses. Differences in management style between genders can be inferred. Male managers are significantly influenced by growth through acquisitions and Pre-IPO planning, with a positive impact. In contrast, female managers show less influence in this regard. Although the network uses probabilistic mathematical equations in its parameterization framework, it was possible to visually observe the implemented model.