Method of determining a remaining time interval until a measurement characteristic of a field device will have drifted outside of a predetermined maximum tolerance and a service action is required, wherein the field device is measuring or monitoring at least one process variable of a medium in a process specific application of automation technology, comprising the steps of: Predetermining the maximum tolerance wherein the measurement characteristic (MC is correlated or related to a measurement performance of the field device, wherein the measurement performance of the field device in the process specific application is unacceptable if the measurement characteristic reaches or exceeds the predetermined maximum tolerance; Registering continuously the measurement characteristic of the field device; Based on the registered measurement characteristics during a given time interval or based on continuously registered data related or correlated to the measurement characteristic of the field device during a past time interval, estimating a lag time interval, wherein the estimated lag time interval depends on the drift of the measurement characteristic of the field device in the process specific application; Using a Monte Carlo Simulation or a method of Artificial Intelligence to, at the end of the estimated lag time interval and based on the registered measurement characteristics, determine the remaining time interval until the measurement characteristic of the field device will have drifted outside the predetermined maximum tolerance and the service action is required; Generating a message informing of the remaining time interval and Using a non-linear transformation (f(t)) of the determined remaining time interval relative to the lag time interval to determine a confidence level CL) wherein the confidence level provides information about the reliability of the determined remaining time interval. Predetermining the maximum tolerance wherein the measurement characteristic (MC is correlated or related to a measurement performance of the field device, wherein the measurement performance of the field device in the process specific application is unacceptable if the measurement characteristic reaches or exceeds the predetermined maximum tolerance; Registering continuously the measurement characteristic of the field device; Based on the registered measurement characteristics during a given time interval or based on continuously registered data related or correlated to the measurement characteristic of the field device during a past time interval, estimating a lag time interval, wherein the estimated lag time interval depends on the drift of the measurement characteristic of the field device in the process specific application; Using a Monte Carlo Simulation or a method of Artificial Intelligence to, at the end of the estimated lag time interval and based on the registered measurement characteristics, determine the remaining time interval until the measurement characteristic of the field device will have drifted outside the predetermined maximum tolerance and the service action is required; Generating a message informing of the remaining time interval and Using a non-linear transformation (f(t)) of the determined remaining time interval relative to the lag time interval to determine a confidence level CL) wherein the confidence level provides information about the reliability of the determined remaining time interval.