The rapid growth of the global population has precipitated a corresponding surge in wastewater production, exacerbating the challenge of managing wastewater treatment sludge. The accumulation of sludge, a complex by-product of treatment processes, poses significant logistical and economic burdens due to its voluminous nature and challenging composition. This study addresses these pressing challenges through a systematic review and comparative analysis of predictive models for Waste Activated Sludge (WAS), focusing on optimising methane production and enhancing energy efficiency in wastewater treatment facilities. Activated sludge models are employed to define sludge characteristics, which guide the implementation of appropriate sludge pretreatment methods, thereby increasing methane production estimation when using Anaerobic Digestion Model No. 1 (ADM1). Mechanistic models such as ASM3 and ADM1, as well as data-driven approaches including Artificial Neural Networks (ANN) and Machine Learning (ML) algorithms, are evaluated comprehensively. ASM3 emerges as a standout model due to its robust theoretical underpinnings and superior predictive accuracy for critical parameters such as Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Total Suspended Solids (TSS) across diverse operational contexts of wastewater treatment plants (WWTPs). Furthermore, the study underscores ASM3’s efficacy in guiding pre-treatment strategies aimed at optimizing sludge characteristics to enhance methane yield. Recommendations include adjusting operational parameters such as sludge retention times (SRT) and implementing advanced hydrolysis techniques to maximize biogas production and improve overall energy recovery from sludge. The findings emphasise ASM3’s efficacy in guiding pre-treatment strategies aimed at optimizing sludge characteristics to enhance methane yield estimation through ADM1, offering practical solutions to mitigate environmental impact and improve energy efficiency in wastewater treatment facilities. This research provides actionable insights for stakeholders and policymakers to implement sustainable practices in wastewater management, aligning with global efforts towards resource conservation and environmental sustainability.