In this study, performances of correct break point estimation of Simple Mean Shift Model Method, Fluctuation Test, Wald Statistic Test and Kim Test methods used to investigate presence of structural break and determine the date of break in a panel data consisting of N time series, each of T length, belonging to N cross-section have been investigated. In this context, 108 Monte Carlo simulations with each 3000 repeats have been carried out for 3, 3, 4 and 3 levels of factors, respectively number of cross-section units, length of series, size of break and proportion of break, to evaluate the performance of these tests used for determination of structural break in panel data. According to the Monte Carlo simulations it is concluded that Simple Mean Shift Model approach has better performance of break point estimation than other methods. Moreover, while Wald Test puts forth its best performance in the case where the breaks in series are at the half of the series, Fluctuation and Kim Tests showed their best performances in the case that the breaks are at the third quarter of series. Generally, correct break point estimation performances of tests decrease as the number of cross-section or length of series increases, even if it is limited. The changes at the levels of the proportion of break factor also lead to high accuracy estimation performance of different methods. Moreover, increases at the size of break usually decreases rates of correct estimation of methods and they approach to zero while means of the series changed 40% and over after break.