Climate change poses significant challenges to humanity, necessitating accurate predictions of future global temperature trends. This paper presents a mathematical modeling framework for forecasting global temperature dynamics, leveraging principles from dynamical systems theory and climate science. We review historical climate data and develop a mathematical model that incorporates key environmental factors, such as greenhouse gas concentrations, solar radiation, and ocean-atmosphere interactions. Through rigorous calibration and validation against observed temperature trends, our model demonstrates robust predictive capabilities. We explore various scenarios to assess the sensitivity of temperature projections to changes in model parameters and external forcings. Our findings contribute to the understanding of climate dynamics and provide valuable insights for informing climate policy and mitigation strategies.