This study delves into uncovering the intricate correlations between diverse factors and olive production yields within the El Oued region, focusing on two distinct time frames : 2000 to 2010 and 2011 to 2021. Employing Pearson correlation coefficients as the analytical tool of choice, we explored the interrelationships between key variables namely, the average agricultural land area, land area specifically allocated for olive cultivation, quantities of utilized manure and fertilizer, average counts of temporary and permanent workers, and the average irrigated agricultural land area—against the backdrop of the average yield of olive cultivation. The outcomes of our investigation unveiled a spectrum of correlation strengths, encompassing both positive and negative associations, for each respective time period. These revelations underline the dynamic nature of the relationships between the examined factors and olive production yields, shedding light on potential influences shaping these agricultural outcomes. To unravel the complex interplay between these variables further, this study employed advanced statistical techniques. Multiple linear regression models were developed to tease apart the contributions of individual variables and their collective impact on olive yields. In parallel, a sophisticated random forest model was also harnessed, offering a comprehensive understanding of intricate interactions within the dataset. The culmination of our efforts yielded invaluable insights into the multifaceted determinants underpinning olive production within the El Oued region. By discerning the nuanced relationships between these factors and their cumulative effects on yields, our findings hold significant promise for enhancing agricultural practices and elevating productivity levels. This research contributes not only to the theoretical realm of agricultural science but also holds practical implications, potentially guiding future strategies to optimize olive cultivation in the El Oued region.