"Wavelets in Prediction" is a comprehensive guide that explores the fundamentals of wavelet theory and its application in forecasting. The book provides a clear and understandable presentation of the properties of wavelets, including one-dimensional and two-dimensional Haar wavelets as well as Daubechies wavelets. It details the algorithm for constructing Daubechies wavelets and the wavelet transformation, supported by illustrative numerical examples. Additionally, a novel algorithm for time series forecasting is introduced, based on wavelet analysis and artificial neural networks. This algorithm is described both theoretically and mathematically and includes simulations using the Matlab program. The book is aimed at students, graduates, researchers, and anyone interested in wavelets and their applications.