## 1 Introduction  
The increasing pace of seawater temperature rise has led to the search for environmentally hardy corals that could be used in restoration initiatives [1]. However, the current means by which coral climate resilience is assessed is retroactive: via documenting the degree of bleaching in stress-prone individuals during surveys or lab experiments [2, 3]. By the time all reefs are surveyed (or all species experimentally tested in the lab), many others will have perished [4]. Ideally, the health of a coral could be known _prior to_ late-stage manifestations of sickness, but at present no such proactive means for predicting coral fate exists despite a large body of literature on the eco-physiology of corals [5, 6]; in most cases, the implicit goal of these studies is to improve predictions of how coral reefs will change in the coming decades, though in no cases to date have molecular eco-physiological data been used to develop analytical tools for forecasting coral persistence. This could stem from the risk of using lab data to make inferences about animal behavior in situ. Even reciprocal transplants and field-based environmental challenge studies inherently create conditions to which corals would never be exposed (e.g., coring with a drill). Nevertheless, insight into the molecular biology of reef corals gained from both in situ and ex situ experiments could perhaps be useful in predictive model building. As an example, if a particular gene is only expressed by bleaching-susceptible corals in the weeks-months prior to onset of bleaching, and never by those that resist this phenomenon,then this mRNA could serve as a biomarker for environmental stress susceptibility that would be useful in formulating predictions [7; 8]. In a series of works on the well-studied, framework-building, relatively resilient Caribbean reef coral _Orbicella faveolata_[9; 10], high-temperature tolerance was found to vary across shelves (inshore vs. offshore), as well as among genotypes. In addition to transcriptome profiling [9], two proteomics approaches, shotgun sequencing [10] and isobaric tags for relative and absolute protein quantification (iTRAQ [11]), were utilized to understand the cellular basis underlying this heterogeneity in thermotolerance observed in situ; proteins involved in lipid trafficking, immunity, and other pathways were found to be important in determining the degree to which distinct genotypes resisted high-temperature-induced bleaching [12; 13]. Despite the insight gained from this multi-Omic approach, the machine-learning (ML) models trained from these datasets were only validated with lab data held back from the artificial intelligence (AI). Given that the experiment featured a mix of coral genotypes from different environments that displayed a range of high-temperature tolerances, we hypothesized that we could use the proteomic data to develop models capable of predicting the bleaching susceptibility of corals in situ. To field-test these models, we sampled replicate _O. faveolata_ genotypes from each of two inshore and two offshore reef sites of the Upper Florida Keys before, during, and after an anomalously high-temperature event in the summer of 2019 (Figure 1), analyzed their proteomes, input the proteomic data into both the ML models of a prior work [11] and those newly constructed herein, and hypothesized that we could diagnose coral bleaching susceptibility at an accuracy > 80%. Figure 1: Map of study sites (**a–d**) and breakdown of field-tracked and lab coral phenotypes (**e–g**). Field sample sizes and the color score legend are both in a. DHW = degree-heating weeks. Panels (**e–g**) present the breakdown of samples from three of the four study reefs (excluding the test site, Crocker Reef) with respect to their bleaching susceptibility, and the values adjacent to the columns signify number of colonies (rather than genotypes) since, in certain cases, colonies of the same genotype demonstrated different thermotolerances.