Introduction1 Drying shrimp is one of the storage methods that, while increasing the shelf life, leads to the production of a versatile product with various uses, from consumption as snacks to use as one of the main components of foods. Drying is preferred over other preservation methods because it offers numerous advantages, including extended shelf life, enhanced microbial stability, convenient consumption, reduced transportation costs, increased value, and product diversity. To accurately model these processes and thus obtain information on factors such as shelf life and energy consumption, it is necessary to determine the product's initial and final temperatures, its geometry and dimensions, and its thermo-physical characteristics. Simulation of different drying processes requires accurate estimation of the effective moisture diffusion coefficient, which is highly dependent on temperature and humidity. Its dependence can be shown by an equation with an Arrhenius structure as an empirical function of humidity and temperature, or by considering the activation energy. It is necessary to have sufficient knowledge about heat and mass transfer characteristics, such as diffusion or penetration coefficient and the heat transfer coefficient to estimate the final temperature and drying time. This study investigated the drying process of peeled farmed shrimp (Litopenaeus vannamei) using a convective hot air dryer. Various parameters such as shrinkage and the effective moisture diffusion coefficient were examined. Materials and Methods A drying device was built to conduct experimental studies on drying shrimp samples. The experiments were conducted on sliced shrimp meat samples at temperatures of 40, 50, and 60 degrees Celsius, with a constant air velocity of 1.5 m/s. The experimental drying models were based on diffusion theory. In these models, it is assumed that the resistance to moisture diffusion occurs from the outer layer of the food. In most cases, Fick's second law was used to describe the phenomenon of moisture penetration. The study used the standard method of immersion in toluene to measure volume changes in the samples. During the drying process, the volume of the samples was measured at 45-minute intervals, and their volume changes were calculated. To measure the moisture content of the samples, each test started by recording the initial weight of the samples using a digital scale with an accuracy of ±0.001 g. During the drying process, the samples were weighed each time their volume was measured. Shrinkage during the drying process is commonly modeled by finding a relationship between shrinkage and moisture, using linear and non-linear models. In most cases, effective permeability is defined as a function of humidity and temperature. For this purpose, curve-fitting methods were employed to analyze the data collected from experimental tests. The appropriate function was extracted by incorporating the Arrhenius equation, which is applicable to most food items. Results and Discussion Based on the results of statistical indices, the linear model was the best model for depicting the relationship between shrinkage changes versus moisture ratio changes among the various experimental models evaluated for shrinkage and drying kinetics. Similarly, the Weibull distribution demonstrated superior performance in expressing variations in moisture ratio over time. A moisture dependent experimental model was used to express the variations in the apparent density of shrimp, resulting in a computed range of 1017-1117 kg m-3. Furthermore, an Arrhenius equation was derived to express the effect of moisture content and temperature on the effective diffusion coefficient of shrimp. According to the results, the effective diffusion coefficient of shrimp exhibited variations ranging from 0.08 ×10-9 m² s-1 to 7.39×10-9 m² s-1. When deriving the effective diffusion coefficient, the impact of the number of terms in Fick's second law on the variation of the moisture ratio was studied. The findings revealed that increasing the number of terms beyond 100 did not significantly affect the model's outputs. Conclusion The linear model had the highest coefficient of determination (R2) among the evaluated shrinkage models, as well as the lowest root mean square error and sum of square error (SSE). This makes it the most optimal model for interpreting shrinkage at the tested temperature levels. The Weibull distribution experimental model proved to be the most suitable for expressing changes in the moisture ratio of shrimp meat slices over time within the evaluated temperature range. The Arrhenius model accurately predicts changes in the effective diffusion coefficient of shrimp slices with respect to temperature and moisture content within the tested temperature range. [ABSTRACT FROM AUTHOR]