The demand for gold never ends. The gold rate trend shows that gold is one of the best investment plans. So it is wise to predict the trend of the gold rate. Different statistical models can be used for suitable modelling and prediction of data. This paper summarizes the idea of gold rate prediction using the LSTM Network. It is always visible that the price of gold follows a nonlinear nature. The prediction of prices is commanding for the proper financial and investment plans. The gold rate fluctuation can be modelled as an exponential curve. Convolutional Neural Networks is one of the best solutions for solving nonlinearities in data and among them RNNs are best suited for time series predictions and estimations. The dataset collected from the World Gold Council is used and results have shown that the proposed architecture is one of the best financial forecasting methods.