In Colombia, the fashion industry faces growth challenges due to annual volatility, causing the need for proactive policies based on profit forecasts to manage the economic, social and political repercussions.This study employs three exponential smoothing methods, including Single Exponential Smoothing "SES", Double Exponential Smoothing "DES", and Holt Exponential Smoothing "HES", to determine the most accurate operating profit forecasting model.The DES and HES models, with specific smoothing parameters, consistently outperform the others, showing low values of mean absolute percentage error "MAPE", "MAD" and "MSD", indicating their competence in profit prediction.Consequently, these models become crucial tools to evaluate the effectiveness of government policies and establish benchmarks to describe and predict profits and financial margins in the Colombian fashion and clothing industry.