The objective of this thesis is to evaluate the significance and impact of applying machine learning models in the energy sector through a real-case example. A multi-energy plant located in Northern Italy, with production of electricity and heat through cogenerators, boilers and photovoltaic generation, connected to the energy networks and to a district heating system, has been analysed. Several regression models have been developed to predict specific system parameters, such as methane gas consumption and thermal energy production. Additionally, attention has been given to the development of the cost function related to the system's operational framework, leading to the understanding that certain strategies are required to improve the system performance.