Being a source of food, raw resources, and jobs, agriculture is essential to the global economy. However, with a growing population, the demand for food production has increased, making it imperative to improve crop yield and sustainability. Since agriculture is greatly influenced by the surrounding natural conditions, we face many challenges in actual agriculture practices. one of the biggest challenges faced by farmers in determining the right crop and fertilizer to use for optimal yield. Efficient technology can be used to increase yields and reduce possible challenges in this area. One approach is to use machine learning techniques to propose crops and fertilizers to farmers based on their unique needs. In this article, we present a crop and fertilizer recommendation system developed using efficient ML models. We link our model with a web application that allows users to input their data and receive personalized recommendations in multiple regional languages. Our system aims to provide farmers with an easy-to-use tool that can help optimize their crop yield and increase sustainability.