A method for developing machine-learning (ML) based tool including initializing an input dataset for undergoing ML based processing. The input dataset is pre-processed by a first model to harmonize features across the dataset. Thereafter, the dataset is annotated by a second model to define a labelled data set. Features are extracted with respect to the data set. A selection of a machine-learning classifier is received through an ML training module to operate upon the extracted features and classify the dataset. A meta controller communicates with one or more of the first model, the second model, the feature extractor and the selected classifier for assessing performance of at least one of first model and the feature extractor, a comparison of operation among the one or more selected classifier, and diagnosis of an unexpected operation with respect to one or more of the first model, the feature extractor and the selected classifier.