The paper analyzes the influence of the rotation speed of a DFIG (Doubly-Fed Induction Generator) wind turbine generator on the temperature in the operating mode and in the idle state, based on one-year data from the SCADA (Supervisory Control and Data Acquisition) system. The aim is to quantitatively determine the intensity and statistical significance of this relationship. The methodology includes data filtering, linear regression and correlation analysis, with the calculation of the Pearson coefficient (r) and the coefficient of determination (R²). The accuracy of the model was assessed by RMSE and MAE, while statistical validation was carried out by ANOVA analysis and residual analysis. The results show a moderately strong positive correlation between rotation speed and temperature (r = 0.7034), with R² = 0.4949 indicating that speed changes explain about 49.5% of the variability. In idle state, the temperature depends mainly on external factors (ambient temperature, wind, solar radiation, humidity and surrounding objects). The proposed model enables reliable temperature prediction in the operating mode and can be used for operation optimization, monitoring and predictive maintenance of wind turbines.