The experiment was conducted to find out the most influential factors affecting pig’s body temperature (PBT). For this purpose, eight environmental parameters and three growth related factors were considered as variables. Two independent experiments were carried out over a period of 92 days in 2017 and 2018. Environmental parameters inside and outside the pig’s barn were recorded using livestock environment management systems (LEMS) and weather sensors, respectively. Infrared sensors were used for measuring PBT. Among these factors, seven environmental parameters, including temperature, CO2, temperature-humidity index inside and outside the pig’s barn and relative humidity inside the barn were taken as input variables for artificial neural networks (ANN) and multiple linear regression (MLR) models due to their good correlation (r≥0.5) with PBT. The performance of the models in predicting pig’s body temperature was determined using statistical quality parameters, including coefficient of determination (R2), root mean square error (RMSE) and mean absolute error (MAE). Result of the study showed that temperature-humidity index is the most and relative humidity inside the room is the least in fluential factors affecting PBT in MLR/ANN models.