Prospects for Applied Mathematics and Data Analysis PAMDA 2836-4449 10.54216/PAMDA https://www.americaspg.com/journals/show/3650 2022 2022 Master's Student - Faculty of Science, Damascus University – Damascus, Syria Sawsan Sawsan Faculty of Science, Damascus University, Damascus, Syria Maissam Ahamad Jdid The efforts of many researchers and scholars have focused on providing appropriate algorithms for generating random numbers and developing them in a manner that suits the need for them, but these algorithms still have advantages and disadvantages, so they are suitable for a specific study and not suitable for another study. The reason for the interest of researchers and scholars in the process of generating random numbers is that random numbers have many scientific and technical applications, starting with generating a series of semi-random numbers, starting from computer simulation to encryption, games of chance, and random samples for statistics and security. In simulation, which is one of the important methods provided by the new science of operations research, the primary reliance is on generating a series of random numbers that follow the regular distribution in the range [0,1], and then converting these random numbers into random variables that follow the probability distribution according to which the system to be simulated works, as the accuracy of the results we obtain from the simulation process depends on the numbers we generate using one of the algorithms. In other words, the appropriate algorithm for the field of study must be chosen from among the algorithms used, which prompted us to prepare this research, through which we will present a reference study of some of the algorithms used to generate random numbers. Where we will highlight the advantages and disadvantages of these algorithms and the most important areas of their use. Then we will calculate the number of these algorithms and compare them. The algorithms that we will discuss in this research are: ➢Middle Square Method. ➢Middle multi-Method. ➢Fibonacci Methods. ➢Linear congruential Methods. 2024 2024 10 27 10.54216/PAMDA.040102 https://www.americaspg.com/articleinfo/34/show/3650