Flood disasters are one of the most devastating natural hazards. Every year they cause numerous deaths and extensive damage to properties and economic systems in different parts of the world. Consequently, flood prediction is a fundamental research topic in the hydrology field. Researches have attempted to address this problem by using various techniques, ranging from model-driven to data-driven approaches. However, the complex and dynamic nature of the flooding phenomena makes its prediction a challenging task. Nowadays, the improvements in computing power have impulsed the application of neural network models in the flood prediction problem, showing a potential success. This work explores five neural network techniques to predict the water levels in Doboj, Bosnia and Herzegovina (B&H).