In the context of Environmental Health, assessing noise pollution is a critical component because excessive noise can lead to adverse health outcomes such as hearing loss, stress, sleep disturbances, and cardiovascular problems. Environmental Impact Assessment (EIA) often incorporates noise prediction and rating methods to understand the potential effects of noise from various sources, such as transportation, industrial activities, construction, and urban development. Accurate noise prediction helps in planning mitigation strategies, designing urban layouts, and formulating policies to protect public health. Among the various techniques used to evaluate noise, two commonly employed methods are the Prediction Method based on Mathematical Models and the Noise Rating (NR) or Noise Criteria (NC) Method. The first method, mathematical noise prediction models, relies on quantitative calculations to estimate noise levels at specific locations based on source characteristics, propagation paths, and environmental conditions. These models are essential in EIA for forecasting noise levels from proposed projects before they are implemented. The process generally starts with the identification and characterization of noise sources, which could be point sources like machinery, line sources such as highways, or area sources including industrial complexes. Each source is assigned a sound power level, which quantifies the acoustic energy emitted. Mathematical models then incorporate factors like distance from the source, geometrical spreading, atmospheric absorption, ground effect, and reflections from nearby surfaces. A widely used example is the ISO 9613-2 method, which predicts the attenuation of sound over distance under outdoor conditions. This method takes into account meteorological conditions, terrain, and obstacles, allowing for a realistic estimation of the noise levels at receptor points such as residential areas or schools. Another approach is the Traffic Noise Model (TNM), which specifically predicts road traffic noise by considering vehicle type, traffic volume, speed, road surface, and surrounding topography. These models are particularly valuable in Environmental Health assessments because they allow planners to estimate the cumulative exposure of populations to noise, enabling the identification of zones at risk. By simulating different scenarios, such as changes in traffic patterns or industrial operations, authorities can implement preventive measures like sound barriers, buffer zones, or operational restrictions to