In the era of the fast exponential increase of internet traffic, thereby, widespread deployment of IP over Optical Transport Network (OTN) necessitates the designing of a robust and stable backhaul network, so that the Services/Clients don’t experience any blackouts and outages from the International Bandwidth. Because of being a terrestrial backhaul transport network, the performance parameter is mostly the Optical Signal to Noise Ratio(OSNR). In this paper, in the 1st phase, motivated by a live real network, it’s been fully designed the Submarine Cable Backhaul Transport Network from Cable Landing Station(CLS) to Destination with working, protection, and restoration path prioritizing the fidelity of the network. In the 2nd phase, collecting the real-time OSNR time series data from the live circuit, an Artificial Neural Network (ANN) Model has been proposed to predict the OSNR to monitor the performance quality. The Model ANN result shows the network capability for better OSNR assessment and forecasting.