This document presents a project to create a reliable crop information system for farmers. It aims to develop a model to increase crop production and an application for farmers to predict the best seasonal and yearly crops, provide historical crop data, and details on seeds and pesticides for predicted crops. The project uses linear regression algorithms and input labels like rainfall, season, soil type, and production data to predict the best yielding crop as the output. It describes a working mobile application model that takes location and soil data from farmers to provide personalized best crop recommendations and information through voice and images. Technologies involved include Scratch, MIT App Inventor, Android App Studio, Java, JavaScript, IBM Bluemix, and machine learning courses.