With growing environmental concerns, the management of energy consumption has become a key focus for production firms. Consequently, increased attention has been directed by decision-makers and academic researchers toward modeling and forecasting energy consumption. However, only a limited number of studies have specifically examined electricity consumption modeling for industrial cases. To address this gap, an analysis was conducted to identify the factors influencing electricity consumption in a specific case from the confectionery industry in France. Multiple linear regression and multiple exponential regression techniques were utilized to establish an equation correlating consumption with various influencing factors. By examining a comprehensive set of factors, including production volume, operating hours, ambient temperature, and water flow of air handling units, a thorough understanding of the relationship between these factors and electricity consumption in significant energy uses was achieved. The analysis of data collected from a representative confectionery plant revealed significant correlations between the influencing factors and electricity consumption. Based on the derived equation, a model was proposed to estimate electricity consumption using the values of these influencing factors. Additionally, a user-friendly interface was designed, enabling plant operators to apply the model with ease. The findings of this study motivated the company to explore decarbonization initiatives, leading to notable energy savings and a positive financial impact. These insights contribute to a deeper understanding of the drivers of electricity consumption in the confectionery industry and offer valuable guidance for developing strategies to optimize energy usage and enhance sustainability in this sector.