Abstract: Energy consumption forecasting plays a crucial role in optimizing industrial processes, reducing operational costs, and promoting sustainability. This study presents a predictive model for industrial energy consumption using machine learning techniques. The model analyzes historical energy usage patterns, environmental factors, and production data to generate accurate forecasts. By leveraging algorithms such as regression models, time-series analysis, and deep learning approaches, the proposed system enhances decision-making for energy management. The results demonstrate improved prediction accuracy, enabling industries to optimize resource allocation and reduce energy wastage. This research contributes to the growing need for efficient and sustainable energy utilization in industrial settings.

Keywords: Industry Energy Consumption Prediction, Electricity consumption, Machine learning, Linear, regression model, Python, Energy consumption, Electricity demand trends, Strategic planning, Energy utilization, Government and industrial stakeholders

| DOI: 10.17148/IJIREEICE.2025.13461