The need to understand the factors influencing financial indicators, especially those associated with business management, is essential for making sound decisions, maintaining good financial health, strategically planning, and effectively managing risks. Purpose: In this research, the impact of management system maturity on the revenue levels of various types of companies in the city of Barranquilla (Colombia) is analyzed. Methods: To do this, the maturity levels of 201 companies were measured for two consecutive years prior to the Covid-19 pandemic. During the research process, inferential statistics and Machine Learning tools were applied. This was done with the purpose of identifying which established financial indicators directly affect the maturity of organizations’ management systems, highlighting revenue and asset levels as those exhibiting behavior that, when more extensive, leads to better economic benefits. Finally, a Bayesian neural network classifier was used to establish the forecasting capacity of financial indicators and provide key information for the continuous improvement of companies. Results: As main findings, it was evidenced that out of the 20 items used to measure the maturity of management systems, 15 showed a statistically significant relationship with the annual income level of the companies. Furthermore, these 15 items achieved an 89.15% of well-classified companies in their income level. Additionally, during the variable selection process with the help of inferential statistics, it was established that the higher the level of implementation of the 15 identified items from the maturity instrument, the greater the economic income of the company.