The textbook "Multinomial Logistic Regression with Fuzzy Parameters" offers an innovative perspective on multinomial logistic regression by integrating the concepts of fuzzy sets. The authors, Amany A. El-Sayed and Hesham A. Abdalla, present two newly developed approaches based on the assumption that the parameters are fuzzy. The first approach is formulated through a goal programming model, while the second is designed as a multi-objective programming model. To evaluate the proposed models, a comprehensive simulation is conducted that examines the performance of the new approaches in comparison to classical methods. The simulation considers 40 different combinations of factors to demonstrate the robustness and efficiency of the models. This book is aimed at professionals and students in the fields of mathematics and natural sciences who are engaged with advanced statistical methods and their applications.