A method for predictive monitoring of the condition of wind turbines, the method comprising the steps of: - selecting at least one wind turbine inside a wind farm and at least one component of the wind turbine; - acquiring SCADA data comprising operational data of the wind farm during a preselected time period, wherein the SCADA data comprises temperature values of the at least one component of the wind turbine during the preselected time period; - processing SCADA data comprising calculating differential data, wherein the differential data is a difference between the temperature values of the selected wind turbine component of the selected wind turbine and an average temperature of the selected wind turbine component in at least two wind turbines in the wind farm; - defining a monitoring time period to monitor the component, wherein the monitoring time interval is shorter than the preselected time period; - extracting features, wherein the extraction of the features comprises calculating at least one predetermined statistic of the differential data during the monitoring time period, and saving the predetermined statistic as a monitoring feature; - testing if at least one monitoring feature exceeds a threshold value, characterized in that the step of the extracting the features further comprises calculating at least one predetermined statistic of the differential data during a reference time period, wherein the reference time period is at least partially overlapping the monitoring time period, and saving the predetermined statistic as a reference feature, wherein the threshold value is a function of the at least one reference feature. - selecting at least one wind turbine inside a wind farm and at least one component of the wind turbine; - acquiring SCADA data comprising operational data of the wind farm during a preselected time period, wherein the SCADA data comprises temperature values of the at least one component of the wind turbine during the preselected time period; - processing SCADA data comprising calculating differential data, wherein the differential data is a difference between the temperature values of the selected wind turbine component of the selected wind turbine and an average temperature of the selected wind turbine component in at least two wind turbines in the wind farm; - defining a monitoring time period to monitor the component, wherein the monitoring time interval is shorter than the preselected time period; - extracting features, wherein the extraction of the features comprises calculating at least one predetermined statistic of the differential data during the monitoring time period, and saving the predetermined statistic as a monitoring feature; - testing if at least one monitoring feature exceeds a threshold value, characterized in that the step of the extracting the features further comprises calculating at least one predetermined statistic of the differential data during a reference time period, wherein the reference time period is at least partially overlapping the monitoring time period, and saving the predetermined statistic as a reference feature, wherein the threshold value is a function of the at least one reference feature. <EOS>