With the increasing global demand for agricultural efficiency, the importance of accurate and well-informed crop planning is highlighted. The objective of the research project, titled "Precision Crop Prediction using Soil and Environmental Analysis," is to develop a system that utilizes machine learning algorithms and extensive datasets to forecast the most suitable crop for a particular region. This system incorporates essential input parameters such as soil NPK values, pH levels, temperature, humidity, and rainfall data. It provides users with valuable insights, including recommended crops for cultivation, anticipated yield per acre, and estimated market prices for the yield. By offering a comprehensive and data-driven solution, farmers can make more informed decisions, optimize resource allocation, and enhance overall agricultural productivity.