Self-organized criticality (SOC), introduced by Bak, Tang, and Wiesenfeld in 1987, describes how complex systems naturally evolve to a critical state without the need for fine-tuned parameters. SOC is observed in diverse phenomena, including financial market fluctuations and forest fires, which exhibit power-law distributions. While traditional models like sandpiles have been instrumental in studying SOC, the Activated Random Walk (ARW) model stands out as a promising candidate due to its universal characteristics. In this talk, we review existing SOC models and present evidence supporting the ARW model’s robustness and versatility in capturing self-organized criticality. This is joint work with Madeline Brown and Christopher Hoffman.