Travelling is part of every individual’s life today. Travelling has become part of people’s life goals. These travels range from short vacations to yearlong round the world trips. There are many reasons why people travel, most of which fall in the broader categories of either business or leisure. People have been travelling for ages and each day attempt to come up with better ways of planning. However, there are many issues that come up when travelling or planning to travel to new places. One of the major issues is not knowing which destinations fits them best and the most optimal route to use. As such most people end up going to popular destinations that are traditionally known. Most systems today are very good at guiding the user on what to do when they get to a certain destination but they do little in identifying the destinations in the first place. This study proposes a natural language processing model that takes in a user’s preferences in terms of factors such a budget and weather and returns a list of predicted destinations for that user. Natural Language Processing is carried out by training a neural network model that detects similarities based on word vectors. The end result is a prediction of destinations suitable for a user based on their personal preferences.