​Metrics-based project management is an emerging trend in the field. This approach is analogous to routine medical check-ups in an individual’s life, where levels of specific substances are measured to assess the likelihood of certain diseases. For instance, elevated blood sugar levels clearly indicate diabetes, whereas high levels of tumour markers are less definitive indicators of cancer. Often, it is necessary to consider additional factors, such as historical values and comparable metrics in other individuals.​ Similarly, in metrics-based project management, metrics that are relatively easy to measure are collected regularly throughout the project lifecycle. These metrics are then analysed to assess the overall ‘health’ of the project and its likelihood of ultimate success. However, the certainty of such assessments varies depending on the nature of the metrics and the criteria used to define project success. This paper proposes the utilisation of Z-sets to infer a project’s ultimate success based on metrics measured throughout its lifecycle.