Artificial neural networks which are inspired by the concept of the biological neurons are commonly used in many applications including in the field of weather forecasting. The neural networks approaches have provided an educated solution to aid in the decision-making process for weather forecasting as well as a viable means of the prediction of raindrop. This paper attempts to determine the suitability and the applicability of artificial neural networks for rain prediction based on temperature, pressure and humidity. Those conditions have been used as input data and solution was classified as percentage of raining. Multilayered perceptron network with three different learning algorithms have been studied. The multilayered perceptron trained using Levenberg Marquardt algorithm has been proven to produce better results with accuracy percentage (99.75%) as compared to back propagation (94.57%).