Rice is Sri Lanka's most popular staple food, and paddy cultivation is one of the country's primary industries, with a substantial impact concentrated in a few large regions. Paddy farming in sri lanka faces several environmental, economic, and human issues. One of the driving factors that directly impact paddy production is temperature. Every stage of the rice plant will be affected by temperature between seeding and harvesting. Rice plants will be positively affected between specified temperature ranges; otherwise, the temperature would have a negative impact on paddy harvest. Using multiple linear regression as a technique, temperature guidance was created using numerical weather prediction (nwp) data and the r programming language to provide temperature forecasts. Numerical weather prediction (nwp) is a method of forecasting the weather based on initial weather conditions by using mathematical models of the atmosphere and oceans. The numerical integration of the governing equations with an initial condition provided by meteorological measurements is used to calculate the time evolution of the atmospheric circulation. With the help of identifying of the relationship between temperature and rice harvest using some acceptable methods, it will make some sense in future research when creating temperature guidance.