A method for developing a prediction device for predicting a biological, clinical or demographic trait of a person from imaging data of said person, characterized in that it comprises the following steps: - determining imaging descriptors (step 10), said step including the following steps: - acquiring multidimensional images of people by means of an imaging apparatus (step 20); and - extracting multidimensional image elements from the acquired multidimensional images to serve as descriptors (step 24); - classifying the predetermined descriptors on the basis of the capability thereof to predict said trait (step 12); - selecting, from among the classified descriptors, a relevant number of the best-classified descriptors that is sufficient to predict said trait (step 14), said step comprising a step for calibrating a selection function of the number of descriptors on randomly permutated data (step 31); and - constructing the prediction device from the selected descriptors (step 16), the step for selecting the relevant number of best-classified descriptors (step 14) comprises the following steps: - selecting a predictive function ( f) (step 30); - applying, for any different numbers of best-classified descriptors, a learning procedure specific to the predictive function ( f) chosen so as to determine parameters of the predictive function ( f) (step 32) so as to optimize the prediction of said trait; - calculating, for said any different numbers of best-classified descriptors, a selection function ( g) for the number of descriptors from parameters of the determined predictive function ( f) (step 34); and - selecting the number of best-classified descriptors that optimizes the selection function ( g) (step 36). - determining imaging descriptors (step 10), said step including the following steps: - acquiring multidimensional images of people by means of an imaging apparatus (step 20); and - extracting multidimensional image elements from the acquired multidimensional images to serve as descriptors (step 24); - acquiring multidimensional images of people by means of an imaging apparatus (step 20); and - extracting multidimensional image elements from the acquired multidimensional images to serve as descriptors (step 24); - classifying the predetermined descriptors on the basis of the capability thereof to predict said trait (step 12); - selecting, from among the classified descriptors, a relevant number of the best-classified descriptors that is sufficient to predict said trait (step 14), said step comprising a step for calibrating a selection function of the number of descriptors on randomly permutated data (step 31); and - constructing the prediction device from the selected descriptors (step 16), the step for selecting the relevant number of best-classified descriptors (step 14) comprises the following steps: - selecting a predictive function ( f) (step 30); - applying, for any different numbers of best-classified descriptors, a learning procedure specific to the predictive function ( f) chosen so as to determine parameters of the predictive function ( f) (step 32) so as to optimize the prediction of said trait; - selecting a predictive function ( f) (step 30); - applying, for any different numbers of best-classified descriptors, a learning procedure specific to the predictive function ( f) chosen so as to determine parameters of the predictive function ( f) (step 32) so as to optimize the prediction of said trait; - calculating, for said any different numbers of best-classified descriptors, a selection function ( g) for the number of descriptors from parameters of the determined predictive function ( f) (step 34); and - selecting the number of best-classified descriptors that optimizes the selection function ( g) (step 36).