The characteristics of modern business are, among other things, numerous changes in the conditions in which the company operates and the presence of a large amount of data that needs to be transformed into useful information. Through quality data processing and their correct organization, the auditor comes to conclusions that provide insight into the problems of the company's operations or actions that can increase the success of the company. Statistical methods of regression, correlation and trend provide auditors with the ability to process large amounts of data with relatively low resources and facilitate the creation of new insights into the company's operations and its environment. This paper investigates methods of regression, correlation and trend, and their application in audit. The first part of the paper gives a general theoretical overview of revision methods and analytical procedures, followed by descriptions of statistical methods of regression, correlation and trend, exclusively from a statistical point of view. The second part of the paper deals with the application of these statistical methods in the audit with presented examples. The basic hypothesis of this paper is that the mentioned statistical methods have a wide application in auditing and that those help auditors in detecting business disruptions, presenting business results and predicting future results. However, it was revealed that they did not find a wide range of applications in the audit itself. Auditors still more often use classical audit methods such as inspection, observation and ect., while analytical procedures, including the above-mentioned statistical methods, are not given enough attention. In this sense, special efforts are needed by statistical experts in order to expand the use of statistical methods, as well as by audit experts in terms of improving the quality of work and increasing the level of their expertise.