Thin film coatings are essential in the production of various industrial devices, significantly enhancing material performance through advanced deposition techniques. This study focuses on estimating the hardness of thin titanium nitride (TiN) films, which serve as protective coatings in industrial applications, by utilizing fuzzy logic. The fuzzy logic approach allows for the incorporation of various input parameters and the handling of uncertainties inherent in experimental data. The results indicate a high degree of accuracy, with the fuzzy logic model showing a percentage error of only 2.25% and an impressive precision of 97.75%. This close agreement between experimental outcomes and predicted values underscores the effectiveness of fuzzy logic in predicting material properties. By improving the predictability and reliability of thin film coatings, such methodologies can contribute to advancements in material science and engineering, leading to the development of more durable and efficient industrial devices. The application of fuzzy logic in this context demonstrates its potential as a valuable tool for material property estimation and process optimization in industrial manufacturing.