Predictive models offer efficient means to manage the quality and safety of highly perishable seafood. Salmon is an increasingly popular seafood, and relies on well managed domestic and international supply chains to minimize growth of spoilage and pathogenic bacteria. While the literature describes predictive models for smoked and modified atmosphere packaged salmon, there are no reported models for spoilage bacteria and Listeria monocytogenes on head-on and gutted (HOG) aerobically-stored Atlantic salmon. Predictive models were developed for microbial and sensorial degradation of HOG Atlantic salmon stored at 0–15 °C until the end of shelf-life. Total Viable Count (TVC) and Pseudomonas spp. had similar growth rates at 0, 5 and 10 °C, but TVC rate was higher at 15 °C. L. monocytogenes growth rate at 0 °C was 0.004 log10 cfu/h, and showed a log-linear increase (R2 = 0.99) to 0.079 log10 cfu/h at 15 °C. Sensory Quality Index (QI) scores were 2.4, 4.5, and 7.2 times greater at 5, 10 and 15 °C, respectively, compared to 0 °C. QI and TVC rates had a relatively strong relationship at 5 (R2 = 0.87), 10 (R2 = 0.80) and 15 °C (R2 = 0.78), compared to 0 °C (R2 = 0.50). These models are potential tools to manage the safety and quality of HOG Atlantic salmon in supply chains.