The marketplace where currencies from every corner of the world undergo trading is known as the foreign exchange market. It enables traders to purchase or sell any money. Foreign currency, or forex, is a unique sector of finance where speculators can expect to make large profits but also face significant hazards. It’s also a rather straightforward market since dealers may make money simply by foreseeing the path of the two-currency rate of exchange. The foreign currency in the marketplace presents difficulties for period projections due to its fluctuating, highly unpredictable, irregular, and chaotic nature. It is challenging to build a reliable model that can both capture existing trends and adapt to new ones as market conditions change continually. In recent times, scholars worldwide have been closely examining the foreign exchange or FOREX market. Owing to its delicate nature, several studies have been carried out in an attempt to precisely forecast future FOREX currency prices. This work analyzes the effectiveness of machine learning models to predict the next day currency exchange rate (USD to INR). In this context, this work implements a RNN model, and a hybrid LSTM model. The accuracy thus calculated is 99.70% by RNN model and 99.79% by LSTM models respectively.