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Soil fertility plays a pivotal role in enhancing agricultural productivity, which serves as the cornerstone of human sustenance and livelihood. Critical soil chemical elements such as nitrogen (N), phosphorus (P), potassium (K), pH, temperature, and moisture significantly influence soil fertility. Achieving a bountiful harvest hinges on accurately assessing soil composition and applying fertilizers judiciously at the right time. However, due to a dearth of expertise and improper fertilizer application practices, many farmers struggle to cultivate high-quality crops. Traditional soil nutrient assessment methods involving laborious soil sampling and laboratory analysis are both time-consuming and costly. This study proposes an efficient Internet of Things (IoT)-enabled soil fertilizer monitoring and recommendation system aimed at providing farmers with data-driven insights into soil parameters and weather conditions, including soil type and characteristics. Utilizing an array of sensors, the system continuously gathers soil fertility data from farm fields, transmitting via Wireless sensor network (WSN) to a cloud-based database. The best fertilizer will be determined based on various parameters for the specific crop. The IoT-enabled system monitors soil parameters (N, P, K, temperature, pH, moisture, soil type, and rainfall) in real-time, facilitating informed decision-making for farmers. Leveraging this data, a predictive model is employed to recommend suitable fertilizer types, tailored to individual soil conditions. By curbing unnecessary fertilizer expenses and reducing reliance on manual labor in crop management, the proposed solution aims to bolster agricultural productivity. Consequently, it is poised to contribute significantly to national agricultural output and economic growth.