This study aims to prove and examine the effect of some variables on poverty. In this study focus on the effect of the unemployment rate, total population and median income towards poverty risk that occurred in Europe in 2014-2018 and 27 countries as samples. To analyze and prove this hypothesis, an empirical test was conducted in the form of prediction with Smart PLS 3.0 on the magnitude of the influence of the Total Population (X1), Median Income (X2), and Unemployment Rate (X3). The data used are secondary data sourced from the European Statistical Recovery Dashboard. The method used to analyze data is the time series data method. The result showed that Total Population is an independent variable that has a postive and significant effect on the Poverty Risk as a dependent variable. It can be seen that the statistical t value of 6.323> from the t table value of 1.978 and this can be proven by the p values of 0.000 and the significance of 0.000 less than 0.05 which means that Total Population (X1) has positive effect and significant towards Poverty Risk in Europe. But, Median Income is an independent variable and the part of income distribution secondary data that doesn’t play the major role of Poverty Risk in Europe for 2014-2018. It can be proven by p values of 0.588 that no significant 0.05 and the statistical t value of 0.542< from t table value of 1.978 which means that Median Income (X2) is not the major effect on the Poverty Risk in Europe in 2014-2018. Unemployment Rate is an independent variable that has a postive and significant effect on the Poverty Risk as a dependent variable. This can be seen that the statistical t value of 3.130 more than the t table value of 1.978 and this can be proven by the p values of 0.002 that less than 0.05 which means that Unemployment Rate (X3) has positive effect and significant towards Poverty Risk in Europe.