Multinomial Probit: The Theory and Its Application to Demand Forecasting covers the theoretical and practical aspects of the multinomial probit (MNP) model and its relation to other discrete choice models. This text is divided into five chapters and begins with an overview of the disaggregate demand modeling in the transportation field. The subsequent chapters examine the computational aspects of the maximum-likelihood estimation and the statistical aspects of MNP model calibration. These chapters specifically describe the properties of the log-likelihood function and the statistical properties of MNP estimators. These topics are followed by a discussion of the mechanical aspects of the MNP model. The closing chapter examines the errors in the estimation of the true parameter value due to lack of data and how these errors propagate to the final prediction. This book will prove useful to econometricians, engineers, and applied mathematicians.