Oil and gas production operations, particularly those involving subsea production systems, are frequently subjected to harsh underwater conditions characterized by low temperatures and high pressures, owing to the placement of most subsea facilities on the seabed. These challenging environmental factors often lead to the formation of gas hydrates, especially in the presence of moisture within the production fluidIn this study, A suggestion is made to employ an underwater wireless sensor network (UWSN) to showcase the viability of real-time monitoring of pipeline health conditions, aiming to mitigate problems associated with hydrate formation in oil and gas pipelines. Additionally, A predictive analytical model for gas hydrate formation in these pipelines is crafted using Aspen HYSYS simulation and Feed-Forward Artificial Neural Network (ANN) modeling. The development of this prediction model and the potential application of UWSN technology in the oil and gas production field could assist operators in making informed decisions regarding intervention processes for addressing hydrate-related challenges in pipelines.