"In an era dominated by mathematical and statistical models, this book unravels the profound significance of these tools in decoding uncertainties within numerical, observational, and calculation-based data. From governmental institutions to private entities, statistical prediction models provide a critical framework for optimal decision-making, offering nuanced insights into diverse realms, from climate to production and beyond. This book Serves as a comprehensive resource in statistical modeling, methodologies, and optimization techniques across various domains. Features contributions from global authors, the compilation comprises 10 insightful chapters, each addressing critical aspects of estimation and optimization through statistical modeling. Covers a spectrum of topics, from non-parametric goodness-of-fit statistics to Bayesian applications, the book explores novel resampling methods, advanced measures for empirical mode, and transient behavior analysis in queueing systems. Includes asymptotic properties of goodness-of-fit statistics, practical applications of Bayesian Statistics, modifications to the Hard EM algorithm, and explicit transient probabilities. Culminates with an exploration of an inventory model for perishable items, integrating preservation technology and learning effects to determine the economic order quantity. This book stands as a testament to global collaboration, offering a rich tapestry of commendable statistical and mathematical modeling alongside real-world problem-solving. It is poised to ignite further exploration, discussion, and innovation in the realms of statistical modeling and optimization"--