The dragonfly algorithm has gained even more traction in the big data era for forecasting stock market patterns and prices. In order to forecast the price trend of stock markets, we gathered data from the stock markets and suggested thorough customization of the featured engineering and dragonfly algorithm. The stock market pre-processing dataset, the application of several featured engineering approaches, and the creation of a unique dragonfly algorithm for stock market trend price prediction make up the comprehension suggested solution. We carried out thorough analyses on commonly used alternative models and came to the conclusion that our suggested solution performs better because of the thorough feature engineering we created. The method predicts stock market trends with an overall high degree of accuracy. The method adds to stock study of research communities in financial and the technical sectors with its thorough design and assessment of the prediction term length, featured engineering and the data pre-processing techniques.