This document summarizes the actions performed under T4.1 - “Personalized Health Modelling and Predictions” in the context of WP4 “Knowledge Management and Modelling in the iHelp Platform” at this phase of the project. The first version of this series of deliverables, i.e., D4.1 - “Personalised health modelling and predictions I”, provided an extended description of the mechanisms and Artificial Intelligence (AI) models that will be implemented for the realisation of personalised health and risk prediction models. The implementation of the ΑΙ algorithms that are being created during the project’s lifecycle highly depend on the provided datasets on which they are trained. At the previous phase of the project, the description of the datasets that are going to be used, drove the actions under this Task towards a concrete description and specification of the AI algorithms and models that will be utilized. In this updated version D4.2 - “Personalised health modelling and predictions II”, the primary data were available for two out of five pilots -namely UNIMAN and MUP- and a sample dataset was provided by the FPG pilot. In this respect, an initial approach of the development of the AI models and some preliminary results are provided in the corresponding sub-sections of Section 6. As in the previous version, this document encapsulates the necessary and relevant information that was researched from recent bibliography to facilitate the manipulation of the available datasets, setting the basis for the design and implementation of the models. Finally, in this deliverable are analysed the main concepts behind the models, also in compliance with an analysis of the importance of known and unknown risk factors based on the description of the clinical/primary data.