Predictive Analytics for Business Growth Using Machine Learning

Abstract

In today’s data-driven economy, organizations rely heavily on data analytics to make informed business decisions. Predictive analytics, supported by machine learning techniques, enables companies to forecast future performance using historical data. This research analyzes how predictive models can be applied to estimate company growth and profitability trends. A dataset containing company performance indicators such as revenue, expenditure, and sales growth was used for experimentation. Machine learning algorithms such as Linear Regression, Random Forest, and Decision Tree were implemented to compare prediction accuracy. The results demonstrate that predictive analytics can significantly improve the accuracy of business growth forecasting and assist managers in strategic planning. The study highlights the importance of integrating machine learning into business intelligence systems to support sustainable decision-making and competitiveness.