In recent years, sustainable and green energy harvesting systems have become critical. Among renewable sources, water-based mechanical energy—such as rainfall and flowing water—remains largely underutilized. Triboelectric nanogenerators have emerged as an efficient technology for converting low-frequency mechanical energy into electrical energy. However, most existing systems are costly or complex. Our work focuses on a simple, low-cost water–solid TENG and evaluates its experimental behaviour along with machine-learning-based performance prediction