This study sheds light on the linear and nonlinear relationship between financial development level and income inequality across 79 countries within a period of 1995 to 2016. To test this relationship panel the Method of Moments Quantile Regression (MMQR), which was recently published by Machado and Silva (2019), has been employed. Besides Pedroni and GUV cointegration tests, FMOLS and DOLS have been administered. Although traditional mean estimators can explain the heterogonous nature of analysed countries, since their results depend on conditional mean they fall short in making the responses heterogonous. In that sense, the effects of specific factors such as financial and economic developments which also impact income inequality have been inspected via MMQR, which also takes into account certain econometric difficulties such as heterogeneity and endogeneity in various quantiles. Compared to other methods, another advantage of MMQR is that by providing information on how explanatory variables can influence the entire conditional distribution, it allows the use of methods only valid in the estimation of conditional means, such as difficulty in noticing heterogeneity and endogeneity problems in panel data models. According to the results obtained from the MMQR model, Greenwood and Jovanovic's (1990) inverted U hypothesis was accepted only in countries with an inequality income distribution between financial development and income inequality, whereas in counties with equal income distribution the income inequality widening hypothesis was confirmed. According to Panel FMOLS and Panel DOLS and also coefficient estimations, Greenwood and Jovanovic (1990)'s inverted U hypothesis was confirmed in the relationship between financial development and income.