In this paper, a single-stage, horizontal type centrifugal pump, which can be used in a chemical tanker's cargo operations, was modelled with MATLAB/Simulink software. The modelled pump was run with seven different fluids handled in chemical tankers which are ethyl alcohol, N-Propyl alcohol, phenol, chloroform, castor oil, 55% nitric acid and water. Therefore, the pump's performance curves and data sets were obtained for each situation. After these, a neural network was created with MATLAB/ Neural Network Fitting Tool application. Inputs of the network were volumetric flow, head, shaft power, torque, and net positive suction head. The output was the pump efficiency and it is estimated for each fluid from the numeric data. Mean squared error was very close to zero (1.1817e-6) and R-2 provided a prediction accuracy of 99.996%. According to these results, artificial neural network (ANN) had a satisfactory performance to predict the efficiency of a chemical tanker's centrifugal cargo pump.