In order to transform cities into more liveable, safe, and sustainable places, we must shift our mobility paradigms. As one auspicious concept amongst urban transportation facilities, para transit modes facilitate urban transportation into small, efficient, and affordable vehicles that are flexibly operated on any infrastructure i.e. specifically motorized three-wheelers being the most prominent subject vehicle of para-transit mode in India, yielding the potential to make public transit more convenient, affordable, and sustainable all at once. Considering this, service quality prediction for motorised three-wheelers at urban roadways is analysed involving the data collected from 50 road segments from 5 cities. Adaptive Neuro Fuzzy Interface System (ANFIS) is used for the development of Three-Wheeler Level of Service (3W-LOS) prediction model, which simplifies the complex and wide input space. The steps involved for 3W-LOS modelling are; defining input-output variables (influencing parameters (Vi) with two- tailed significance (p)<0.001), defining fuzzy sets for input values (f(Vi)), defining fuzzy rules (Weights towards rules and input functions (Wi)), create and train the neural network using Gaussian membership function. The coefficient of determination for training and testing is found to be 0.8809 and 0.8239 respectively by using the ANFIS output for 3W-LOS prediction over Indian roadway segments.