A method, performed by a fault localization system, for predicting a location of a fault in a computer system, the method comprising: receiving a sample of machine-level metrics relating to the computer system, mapping the sample to an initial unit of the SSOM; obtaining a faulty unit pertaining to a Supervised Self-Organizing Map, SSOM, and wherein the faulty unit has been derived from a sample of machine-level metrics relating to the computer system, wherein the SSOM has been trained with a first layer of machine-level metrics and a second layer of service-level metrics, wherein the trained SSOM includes at least one faulty unit and at least one normal unit, wherein the method is characterized by: expanding a radius of a circle originating at the faulty unit until a predefined number of normal units of the SSOM falls within the circle, computing, for each machine-level metric, a respective score based on differences between the faulty unit and the predefined number of normal units, wherein a set of scores comprises the respective score for each machine-level metric, and selecting a sub-set of the set of scores, wherein the sub-set comprises a number (k) among the greatest scores of the set of scores, whereby the location of the fault is predicted to be located to one or more machine-level metrics represented by the sub-set of scores. receiving a sample of machine-level metrics relating to the computer system, mapping the sample to an initial unit of the SSOM; obtaining a faulty unit pertaining to a Supervised Self-Organizing Map, SSOM, and wherein the faulty unit has been derived from a sample of machine-level metrics relating to the computer system, wherein the SSOM has been trained with a first layer of machine-level metrics and a second layer of service-level metrics, wherein the trained SSOM includes at least one faulty unit and at least one normal unit, wherein the method is characterized by: expanding a radius of a circle originating at the faulty unit until a predefined number of normal units of the SSOM falls within the circle, computing, for each machine-level metric, a respective score based on differences between the faulty unit and the predefined number of normal units, wherein a set of scores comprises the respective score for each machine-level metric, and selecting a sub-set of the set of scores, wherein the sub-set comprises a number (k) among the greatest scores of the set of scores, whereby the location of the fault is predicted to be located to one or more machine-level metrics represented by the sub-set of scores. expanding a radius of a circle originating at the faulty unit until a predefined number of normal units of the SSOM falls within the circle, computing, for each machine-level metric, a respective score based on differences between the faulty unit and the predefined number of normal units, wherein a set of scores comprises the respective score for each machine-level metric, and selecting a sub-set of the set of scores, wherein the sub-set comprises a number (k) among the greatest scores of the set of scores, whereby the location of the fault is predicted to be located to one or more machine-level metrics represented by the sub-set of scores.