Avocados’ shelf life is limited and difficult to monitor. This study evaluated the performance of chitosan coatings (1.5 and 2% w/v, T1 and T2) on avocados’ quality and shelf life against samples untreated (C) and treated with an ethylene inhibitor (1-MCP, M). Hyperspectral imaging (HSI) coupled with machine learning (ML) techniques was also evaluated to estimate Hass avocados’ quality indicators. Sensorial, physicochemical, and metabolic characteristics were measured using standard procedures. While T2 samples exhibited undesirable changes (i.e., uneven color and heterogeneous firmness), T1 behaved similarly to C. However, neither treatment could delay senescence as much as 1-MCP (42 vs ≤ 33 days). In general, Bayesian regularization neural networks (BRNNs) outperformed the other tested ML techniques in estimating quality attributes from HSI features, allowing for real-time nondestructive assessment of food quality. Adverse effects of chitosan coatings on avocados’ physiology were identified, which can inform the development of films with improved performance.