This study focuses on analysis of trip generation (TG) of Tier II Cities in Madhya Pradesh, India, namely Bhopal and Jabalpur. The collection of household data is conducted via a questionnaire survey. Multilinear Regression (MLR) and Artificial Neural Network (ANN) are utilized to found that six dominant variables affect the household TG. The MLR dataset was used to create, test, and compare ANN models for each municipality. The ANN model with r square value of 0.604 and 0.686 and mean square error (MSE) of 458.62 and 254.63 performed better than the MLR model (R2 = 0.48 and 0.59 and MSE = 1573.33 and 1569.98) for Bhopal and Jabalpur respectively. The findings suggest that ANN is a practical tool for TG modeling, with predictions that are even more solid than those of traditional MLR. The TG model provides precise TG calculations and facilitates in providing transportation infrastructure facilities by policy makers.