Modern agriculture requires an effective nutrient management system for the soil, which can be done by using IoT sensors. The proposed system integrates IoT sensor technology with machine learning (ML) algorithms for effective crop recommendations. The system incorporates the latest techniques to handle the challenges in modern agriculture by taking real-time soil data, moisture, and NPK content through its deployed sensors. Grouping the data, it is then processed and analyzed using machine learning models trained on a large-scale agricultural dataset. The proposed system provides tailored recommendations for the crops based on nutrient values of the soil, which will be collected by the IoT sensors. In this work, a user-friendly web application has been built to provide insights to farmers to promote sustained development and sustainable farming. This work aims to increase agricultural productivity, lessen resource waste, and minimize environmental degradation. The results show enhanced yields, fertilizer cost savings, and improved sustainability in farming. This novel method of precision agriculture marks a turning point in the revolution of the agricultural sector by feeding a growing number of people, leading towards global food security and environmental conservation.