Porosity assessment is essential for reservoir characterization. While laboratory measurements and conventional well-logs have traditionally been used to estimate porosity, they may not always provide accurate results in carbonate reservoirs, due to their extremely heterogeneous pore system. This is where nuclear magnetic resonance (NMR) tools offer a valuable solution. NMR logging technology allows for more accurate quantification of different porosity types, including total, effective, and free-fluid porosity. However, acquiring NMR logs can be costly and challenging due to factors such as the activation of wireline equipment, signal-to-noise ratio, environmental factors, and the properties of the formation fluid. To overcome these challenges and provide an alternative approach, we are interested in developing predictive models, using conventional well-logs as input data.