Sensors in and around the environment becoming ubiquitous has ushered in the age of smart animal agriculture which has the potential to greatly improve animal health and productivity. The data gathered from sensors dwelling in animal agriculture settings have made farms a part of the IoT space leading to active research in developing efficient communication methodologies for farm networks. This study focuses on the first hop of farm networks where data from inside the body of animals is communicated to a node dwelling outside the body. Novel experimental methods are used to calculate the channel loss at sub-GHz frequencies (100-900 MHz) to characterize the in-body to out-of-body (IBOB) communication channel in large animals. A first-of-its-kind 3D bovine modeling is done with computer vision techniques for detailed morphological features of the animal body to perform Finite Element Method based Electromagnetic simulations. The results of the simulations are experimentally validated to build a complete channel modeling methodology for IBOB animal-body-communication. The 3D bovine model is made available publicly on GitHub. The results illustrate that an IBOB communication channel is realizable from the rumen to the collar of ruminants with [Formula: see text] path loss at sub-GHz frequencies making communication feasible. The developed methodology has been illustrated for ruminants but can also be used for other IBOB studies. An efficient communication architecture can be formed using the channel modeling technique illustrated for IBOB communication in animals paving the way for the design and development of future smart animal agriculture systems.