Flow controllers are widely used in various industries, such as in the petroleum industry to drain oil from offshore to onshore or used for oil distribution. The most used flow controllers in industries are PID-based controller that are implemented using PLCs. In this study, Neuro-Fuzzy controller, designed based on ANFIS algorithm, with inputs in the form of error and change of error, from the observed process variable, which in this case is the water flow rate in the prototype plant output pipe. The controller is operated in the MATLAB/SIMULINK environment on the PC, which gets flow rate information from flowmeter that connected to the PLC. PLC communicated with the controllers through OLE for Process Control(OPC) facility. The output of the controller, which is in the form of a control valve opening, will be delivered to the PLC via OPC. Therefore, the PLC can control the valve opening according to the desired water flow rate. After undergoing the training process, the developed ANFIS-based controller tested with various of the water flow rate set point to obtain its performance information. From this study it was found that ANFIS-based controller is a controller with good performance, which has the average rise time is 14.76 s, the settling time is 26.82 s, and with overshoot of 1.9%, and has a relatively small error of 1.75%.