Temperature, a critical measure of heat and cold, is vital in understanding climate dynamics. The Celsius scale is widely recognized for temperature measurement, and its implications become increasingly relevant as climate change accelerates, primarily due to human activities like deforestation, specific farming practices, and industrial waste production, which elevate greenhouse gas concentrations in the atmosphere. The excessive presence of these gases has pushed global temperatures to unprecedented levels, instigating climate shifts characterized by convection, wind patterns, cloud formation, and precipitation changes. Temperature variations across different regions and time periods stem from an array of factors, including solar radiation, ground conditions, ocean currents, geographic location, and cloud cover. The challenges posed by temperature variability and climate instability have spurred extensive research into developing precise weather forecasting models. This study focuses on Bangkok, Thailand's bustling capital and economic hub, given its pivotal role in the nation's GDP contribution. By employing simple time series analysis, this research aims to construct statistical models for predicting daily maximum and minimum temperatures in Bangkok. These models hold the potential to benefit future planning efforts, empower residents to prepare for meteorological phenomena, and mitigate associated challenges and losses. In an era of changing climates, the foresight gained from such endeavors proves invaluable