This study describes the application of a hybrid neuro-fuzzy inference system to control electrospinning process and how to use this approach for developing an electrospun fiber quality prediction system. An adaptive neuro-fuzzy inference system model has been applied to the use of electrospinning process parameters to study the relationship between electrospinning processing parameters and electrospun fiber morphology. Fiber morphology has been predicted and the impact of each processing parameter has been investigated. It was found that four electrospinning process parameters including: polymer solution concentration, spinning distance, applied voltage, and volume flow rate are the most influential factors to the electrospun fiber morphology. It was observed that the relationship existing between electrospinning processing parameters and nanofiber morphology is nonlinear.