According to the report, around 47% of the damage to offshore steel pipelines in China is caused by corrosion defects, as shown in Fig. 2.1 (Zhang et al. J Fail Anal Prev 14(4), 530–536, 2014 [1]). In this chapter, the critical need for accurate reliability assessment of corroded pipelines, essential for transporting energy resources, is addressed. Despite extensive research, the interaction between adjacent corrosion defects and the effects of corrosion depth and steel grade on pipeline integrity have been inadequately explored. A novel reliability assessment method is introduced, integrating finite-element analysis, regression, burst pressure models, Monte Carlo simulation, and artificial neural networks to fill this gap. This comprehensive approach refines interaction rules considering corrosion characteristics and enhances prediction efficiency and accuracy. By applying this method to a case study, advancements in pipeline safety management are pursued, aiming to establish a new benchmark for the industry's reliability standards.