Emerging contaminants often occur at low concentrations and complex matrices [11]. Numerous laboratory studies have reported the inability of most analytical instruments to capture and quantify low levels of antibiotics [12; 13; 14; 15; 16]. Hence, continuous tracking of the level of contaminants in the environment is essential for sustainable water management. However, direct measurement of contamination levels requires considerable investment, extensive laboratory technology, and labor. Consequently, analytical and mathematical methods are employed in these efforts. Moreover, analytical determination of low concentrations of antibiotics necessitates sophisticated high-resolution equipment, which requires specialists to operate and is not easily affordable. Mathematical modeling and simulations are effective tools for studying the fate and transport of contaminants. Mathematical models can evaluate low, barely detectable antibiotic concentrations and continuously observe (temporal coverage) contamination levels in the aquatic environment [17; 18]. Additionally, the development and use of a mathematical model describing the physical, chemical, and biological interaction processes provide the ability to evaluate \"what if\" scenarios and to compare exposure assessments (human and microorganism). Moreover, these models provide greater spatial coverage and can be used for observations where accessibility is difficult. However, model predictions have many uncertainties regarding model input values, simplifications of complex processes, calibration, and corroboration [19]. Mathematical modeling faces challenges in representing the complex interaction between contaminants and the environment, requiring further development through continuous improvement and investigation. A pollutant that enters a river system undergoes numerous events during transport as it interacts with many biological, environmental, and weather elements. In instantaneous or long-period interaction, the pollutant mass entering the water bodies might be either lost through various in-stream reaction mechanisms or transformed into other compounds via chemical and biochemical reactions. The pollutant mass in waterbodies can also escape by evaporation, volatilization, sedimentation, and flow abstractions without changing its chemical composition. Further, pollutant compounds have distinct properties while reacting with different environmental compartments. Some compounds have an affinity to the water phase and the solid, while others are more attracted to either the solid or the liquid phase, and others are highly volatile. The fate of antibiotic compounds in the environment is impacted by seasonality, organic and inorganic nutrient accumulation, compound transformation, oxygen demand in the water and underlying sediment, presence of bacteria, algal and pathogen growth, climate, and flow variabilities. These biological, environmental, chemical, and weather factors determine their destination and fate [20; 21; 22; 23]. Hence, the system representation of the dynamic pollutant degradation mechanisms has evolved into complex modeling to reduce prediction uncertainties. Several mathematical models have been developed worldwide to simulate the fate of antibiotics in the aquatic environment. Most of these models are process-based and use a set of mathematical formulations to combine existing theories, principles, and empirical knowledge of physical, biological, chemical, and ecological phenomena and are composed of tools and systems to simulate the fate of antibiotics realistically [24]. The use of these models necessitates a broad and interdisciplinary understanding of their simulation mechanism, parameter estimation, data requirement, and validation, as well as strengths and limitations, to know the applicability and prediction uncertainties. This study critically reviews the source, natural attenuation mechanism of frequently detected antibiotic groups, and the state-of-the-art on development and applicability of environmental fate and transport models.