Almost every industrial and service enterprise adopts some form of Environmental Health and Safety (HSE) practices. However, there is no unified measurement implementation framework to resist losses exacerbated due to the “lack of safety precautions”, which must be considered one of the most dangerous Lean wastes because it jeopardizes the investment in the HexBottom-Line (HBLs). Despite the widespread nature of the Lean approach, there no unified and collected framework to track and measure the effectiveness of the safety measures’ progress. Therefore, the enterprises resort to establishing their own tailored safety framework that maintains their competitiveness and sustainability. The enterprises must provide insight into safety deficiencies (i.e., faults and losses suffered) that have been measured via downtime spans and costs (Lean waste), reflecting the poor Lean Safety Performance Level (LSPL). This paper aims to shed light on two issues: (1) the adverse impact of the “lack of safety precautions” on LSPL caused by the absence of (2) a Lean Safety framework included in the Measurement and Analysis phases of Define Measure Analyze Identify Control (DMAIC). This framework is based on forecasting losses and faults according to their consumption time. The proposed framework appreciates the losses’ severity (time consumption and costs) via Fault Mode and Effect Forecasting (FMEF) aided by Artificial Neural Networks through sequential steps known as Safety Function Deployment (SFD).