Machine learning has become indispensable in predicting cryptocurrency prices, leveraging various models to capture and forecast market trends. Regression models such as linear regression and polynomial regression analyze historical data to identify patterns and extrapolate future price movements. Time series forecasting models like ARIMA (AutoRegressive Integrated Moving Average) and LSTM (Long Short-Term Memory) are adept at handling the sequential nature of price data, incorporating factors like volatility and seasonality. These models, powered by vast datasets and advanced algorithms, offer valuable insights to investors and traders navigating the volatile landscape of digital currencies. As cryptocurrencies continue to evolve, so too will the sophistication and effectiveness of these machine learning techniques in predicting their prices.