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Machine learning and statistical modeling methods were used to analyze theimpact of climate change on financial wellbeing of fruit farmers in Tunisia andChile. The analysis was based on face to face interviews with 801 farmers.Three research questions were investigated. First, whether climate changeimpacts had an effect on how well the farm was doing financially. Second, ifclimate change was not influential, what factors were important for predictingfinancial wellbeing of the farm. And third, ascertain whether observed effectson the financial wellbeing of the farm were a result of interactions betweenpredictor variables. This is the first report directly comparing climate changewith other factors potentially impacting financial wellbeing of farms. Certainclimate change factors, namely increases in temperature and reductions inprecipitation, can regionally impact self-perceived financial wellbeing offruit farmers. Specifically, increases in temperature and reduction inprecipitation can have a measurable negative impact on the financial wellbeingof farms in Chile. This effect is less pronounced in Tunisia. Climate impactdifferences were observed within Chile but not in Tunisia. However, climatechange is only of minor importance for predicting farm financial wellbeing,especially for farms already doing financially well. Factors that are moreimportant, mainly in Tunisia, included trust in information sources and priorfarm ownership. Other important factors include farm size, water managementsystems used and diversity of fruit crops grown. Moreover, some of theimportant factors identified differed between farms doing and not doing wellfinancially. Interactions between factors may improve or worsen farm financialwellbeing.

Factors other than climate change are currently more important in predicting how well fruit farms are doing financially