A method for monitoring the health of a mechanical system equipping a vehicle, said mechanical system comprising at least one moving member as well as at least one vibration sensor emitting a vibration signal, said mechanical system or said vehicle comprising at least one context sensor emitting a context signal relating to at least one context parameter, said at least one context parameter being chosen from a list comprising at least one or more functional parameters of said mechanical system, one or more navigation parameters of said vehicle and one or more atmospheric parameters, said method being composed of an initial phase of defining a threshold variation model as a function of said at least one context parameter followed by a phase of operational monitoring of the mechanical system, said initial phase comprising the following steps: - taking measurements of successive initial vibration values from said at least one vibration sensor and successive initial context values from said at least one context sensor, - determining, with a calculator (5, 55), several initial health values of at least one health indicator CI relating to said mechanical system as a function of said initial vibration values, each initial health value being associated with one of said initial context values of said at least one context parameter, - defining, for each health indicator CI, a threshold variation model, said threshold variation model being defined as a function of said initial health values of said health indicator CI and said initial context values of said at least one context parameter, by partitioning a domain formed by said initial context values of said at least one context parameter into several ranges of values for which said threshold relating to said health indicator CI is statistically constant over each range of values, each range being associated with several of said initial context values, and by determining values of said threshold with a method using regressions on parameters of quantile distributions conditioned on context parameters and domain decompositions of said at least one context parameter using at least one decision tree, said operational monitoring phase comprising the following steps during the operation of the mechanical system: - taking measurements of successive operational vibration values from said at least one vibration sensor and successive operational context values from said at least one context sensor, - determining, with said calculator (5, 55), an operational health value of at least one health indicator CI as a function of said operational vibration values, said operational health value of at least one health indicator CI being associated with one of said operational context values relating to one or more context parameters, - determining said threshold specific to said operational health value of said at least one health indicator CI using said threshold variation model and said at least one associated operational context value, - triggering an alert signalling a risk of presence of a fault in said mechanical system if said operational health value of said at least one health indicator CI is greater than said determined threshold. - taking measurements of successive initial vibration values from said at least one vibration sensor and successive initial context values from said at least one context sensor, - determining, with a calculator (5, 55), several initial health values of at least one health indicator CI relating to said mechanical system as a function of said initial vibration values, each initial health value being associated with one of said initial context values of said at least one context parameter, - defining, for each health indicator CI, a threshold variation model, said threshold variation model being defined as a function of said initial health values of said health indicator CI and said initial context values of said at least one context parameter, by partitioning a domain formed by said initial context values of said at least one context parameter into several ranges of values for which said threshold relating to said health indicator CI is statistically constant over each range of values, each range being associated with several of said initial context values, and by determining values of said threshold with a method using regressions on parameters of quantile distributions conditioned on context parameters and domain decompositions of said at least one context parameter using at least one decision tree, - taking measurements of successive operational vibration values from said at least one vibration sensor and successive operational context values from said at least one context sensor, - determining, with said calculator (5, 55), an operational health value of at least one health indicator CI as a function of said operational vibration values, said operational health value of at least one health indicator CI being associated with one of said operational context values relating to one or more context parameters, - determining said threshold specific to said operational health value of said at least one health indicator CI using said threshold variation model and said at least one associated operational context value, - triggering an alert signalling a risk of presence of a fault in said mechanical system if said operational health value of said at least one health indicator CI is greater than said determined threshold.