This paper presents an Intelligent Decision Support System (IDSS) to enhance the management of Analytical Laboratories (AL) of a company operating in the chemical industry. This IDSS incorporates two predictive Machine Learning (ML) models, related with the prediction of the arrival of samples at the AL and the consumption of AL materials, which are then used to perform prescriptive analytics for AL instrument allocation tasks. The IDSS is also complemented with descriptive analytics of instrument similarities regarding the tests performed for better supporting the AL manager decisions. The IDSS includes interactive dashboards and it was successfully validated by the AL managers using the Technology Acceptance Model (TAM) 3 and open interviews, which resulted in a positive feedback.