This book is divided into two parts. The first part introduces the MATLAB realization of conventional methods (fitting, AHP), programming model, data modeling (cloud model, logistic, principal component analysis, support vector machine, K-means, naive Bayes) and grey prediction in mathematical modeling, as well as the MATLAB realization of various advanced methods, including genetic algorithm, simulated annealing algorithm, artificial neural network, particle swarm optimization, ant colony algorithm, wavelet and computer simulation. The second part takes the mathematical modeling contest as an example, introduces how to solve the practical mathematical modeling problem with MATLAB, and gives the detailed modeling process and MATLAB source program. The appendix of the book introduces the author's experience of winning many awards in the modeling competition, and I believe these experiences are very helpful to the students who are preparing to participate in the mathematical modeling competition.