The study conducted in India using Fuzzy Inference System (FIS) is a novel approach to predicting traffic accident rates on rural highways. By using various highway geometric elements as input data, the study was able to identify risk variables related to roadway features and predict accident rates using FIS. The findings of the study suggest that FIS is a valuable tool for predicting accident rates and can help identify the factors that contribute to accidents. The study also found statistically significant positive connections between geometric elements and accident rates, which highlights the importance of highway design and safety measures. The use of Fuzzy Inference Systems in accident prediction is a promising approach as it allows for a more comprehensive understanding of the complex relationships between various factors contributing to accidents. The model was tested using simulation and data analysis and was found to fit well with real-world data, indicating its potential for practical applications in road safety management. Overall, this study provides important insights into the use of FIS in predicting accident rates on rural highways and can help guide future research in this area. It also highlights the importance of considering various highway geometric elements in designing safer highways and implementing appropriate safety measures to reduce accident rates. However, the road accidents can have significant impacts on ecological cycles, including habitat fragmentation, wildlife mortality, pollution, and climate change.