This book provides an introductory albeit solid presentation of path integration techniques as applied to the field of stochastic processes‎.‎ The subject began with the work of Wiener during the 1920‎'‎s‎,‎ corresponding to a sum over random trajectories‎,‎ anticipating by two decades Feynman‎'‎s famous work on the path integral representation of quantum mechanics‎.‎ However‎,‎ the true trigger for the application of these techniques within nonequilibrium statistical mechanics and stochastic processes was the work of Onsager and Machlup in the early 1950‎'‎s‎.‎ The last quarter of the 20th century has witnessed a growing interest in this technique and its application in several branches of research‎,‎ even outside physics ‎(‎for instance‎,‎ in economy‎)‎‎.‎ The aim of this book is to offer a brief but complete presentation of the path integral approach to stochastic processes‎.‎ It could be used as an advanced textbook for graduate students and even ambitious undergraduates in physics‎.‎ It describes how to apply these t‎.‎‎.‎‎.‎