This paper presents an exploratory data analysis and prediction model for fuel prices in the Federation of Bosnia and Herzegovina (FBiH) relative to oil price movements. The study focuses on the Super 98 fuel type and utilizes data collected from the Federal Ministry of Trade of BiH’s eOPC application from December 2018 to September 2023. The analysis employs various data visualization techniques and statistical methods to identify trends and correlations. A recurrent neural network, specifically a long-short-term memory (LSTM) model, is constructed to predict future fuel prices based on historical data and the movements of BRENT and WTI oil prices. The results indicate a high correlation between fuel prices in FBiH and BRENT oil prices, with the LSTM model demonstrating high predictive accuracy. This research provides valuable insights for decision makers in the economics and energy sectors and suggests potential future research directions, but also publicly publishes and analyzes an official Ministry dataset over a period of 5 years for 716 gas stations and six fuel types.