A method for fetal weight estimation, comprising the following steps: a) Ultrasonically measuring fetal biometric parameters, particularly fetal head, abdominal and limb dimensions of sample cases; b) Determining further physiological and phenomenological pregnancy parameters of these sample cases; c) Determining the fetal weight of the sample cases by precision weighing at birth; d) Creating a database of these known sample cases, in which each record associated to each known case comprises the fetal biometric parameters, the additional physiological and phenomenological pregnancy parameters and the fetal weight as determined at birth; d1) Generating mathematical prediction models from the database of known cases; e) Ultrasonically measuring said fetal biometric parameters, particularly fetal head, abdominal and limb dimensions of the cases under examination, for which fetal weight is to be predicted; f) Determining further physiological and phenomenological pregnancy parameters of these cases under examination, for which fetal weight is to be predicted; g) Predicting the fetal weight of said cases under examination by using the mathematical prediction models generated in step d1), and h) displaying the neonatal weight estimate; characterized in that a multinormal probabilistic model is used as a mathematical model, the said multinormal probabilistic model is the following function giving the probability density of measured fetal biometric parameters and one or more physiological and phenomenological pregnancy parameters, which probability density is conditioned by the information relating to further physiological and phenomenological pregnancy parameters and to fetal weight: p x / w = 1 2 π d / 2 ∑ w 1 / 2 exp − 1 2 x − μ w T ∑ w − 1 x − μ w where: x is the observation vector, including measured ultrasound biometric parameters of the fetus and one or more physiological and phenomenological pregnancy parameters, which observation vector comprises, as components, the variables xi, i=1,2,... n, each relating to one of the measured ultrasound biometric parameters of the fetus and of the one or more physiological and phenomenological pregnancy parameters. w is the data vector containing, as components, the variables wj, j=1,2,...,k, each being composed of the weight at birth and of one of the other physiological and phenomenological pregnancy parameters; d is the dimension of the multidimensional space of the measured ultrasound biometric parameters of the fetus, and one or more physiological and phenomenological pregnancy parameters which form the components of the vector x, with d=n; μ(w) and ∑(w) are the mean vector and the covariance matrix respectively of the mean value xim of the components xi of the data vector x, i.e. of said ultrasound biometric parameters and one or more physiological and/or phenomenological pregnancy parameters, as functions of said data vector w, i.e. of the fetal weight and of the other physiological and/or phenomenological pregnancy parameters that form its components. a) Ultrasonically measuring fetal biometric parameters, particularly fetal head, abdominal and limb dimensions of sample cases; b) Determining further physiological and phenomenological pregnancy parameters of these sample cases; c) Determining the fetal weight of the sample cases by precision weighing at birth; d) Creating a database of these known sample cases, in which each record associated to each known case comprises the fetal biometric parameters, the additional physiological and phenomenological pregnancy parameters and the fetal weight as determined at birth; d1) Generating mathematical prediction models from the database of known cases; e) Ultrasonically measuring said fetal biometric parameters, particularly fetal head, abdominal and limb dimensions of the cases under examination, for which fetal weight is to be predicted; f) Determining further physiological and phenomenological pregnancy parameters of these cases under examination, for which fetal weight is to be predicted; g) Predicting the fetal weight of said cases under examination by using the mathematical prediction models generated in step d1), and h) displaying the neonatal weight estimate; x is the observation vector, including measured ultrasound biometric parameters of the fetus and one or more physiological and phenomenological pregnancy parameters, which observation vector comprises, as components, the variables xi, i=1,2,... n, each relating to one of the measured ultrasound biometric parameters of the fetus and of the one or more physiological and phenomenological pregnancy parameters. w is the data vector containing, as components, the variables wj, j=1,2,...,k, each being composed of the weight at birth and of one of the other physiological and phenomenological pregnancy parameters; d is the dimension of the multidimensional space of the measured ultrasound biometric parameters of the fetus, and one or more physiological and phenomenological pregnancy parameters which form the components of the vector x, with d=n; μ(w) and ∑(w) are the mean vector and the covariance matrix respectively of the mean value xim of the components xi of the data vector x, i.e. of said ultrasound biometric parameters and one or more physiological and/or phenomenological pregnancy parameters, as functions of said data vector w, i.e. of the fetal weight and of the other physiological and/or phenomenological pregnancy parameters that form its components.