This paper studies the use of wavelet transform and curve fitting methods for solar radiation compression and prediction-based modeling. Symlet 6 and Meyer wavelets will be utilized for analyzing the transient nature of solar radiation. The measured solar radiation data will be decomposed up to level 4. After the data has been filtered, curve fitting method will be used to derive the modeling equation to estimate the horizontal global solar radiation. The instantaneous global solar radiation received on the surface of earth in Malaysia on a clear sky day around noon time can be up to 980 W/m 2. The amount of solar energy received is highly transient in nature, due to the meteorological conditions. Therefore data captured using electronic data acquisition system is quite dense, and there is a need to filter the data, in order to reduce the amount of dataset. The data is highly useful for the designing of solar energy related electricity generation systems. The accuracy of the predicted output from a photovoltaic (PV) based electricity generation system depends on the accuracy of the intercepted solar radiation. The sizing of the electricity generating system cannot be based on a single power density value. Therefore compressed time based solar radiation values serve as an important input for the designing of a PV based system during the availability of sunshine. © 2011 IEEE.