Applying neural networks to forex price prediction enhances market analysis by identifying complex patterns in historical price data. These models, particularly deep learning architectures like LSTMs and CNNs, excel at capturing nonlinear relationships and trends, improving forecasting accuracy. Unlike traditional statistical models, neural networks adapt to changing market conditions, learning from vast datasets to refine predictions. By incorporating technical indicators, sentiment analysis, and macroeconomic factors, these AI-driven systems provide traders with a data-driven approach to decision-making. However, challenges remain, including overfitting, data quality issues, and market unpredictability. Despite these hurdles, neural networks continue to revolutionize forex trading, offering a powerful tool for navigating the complexities of currency markets and enhancing predictive performance.