The increasing generation of agro-industrial by-products from fruit processing represents both an environmental challenge and a valuable opportunity for resource recovery. In this study, tomato, apple, and orange by-products were selected as sustainable substrates for valorization through lactic acid bacteria (LAB) fermentation. The objective was to enhance their functional potential while contributing to waste reduction within a circular bio-economy framework. Selected Lactiplantibacillus plantarum strains were applied to each matrix, and microbial growth dynamics were monitored throughout fermentation. In parallel, experimental data were used to build and validate machine learning-assisted models to predict growth kinetics and identify optimal fermentation conditions. To validate the model, the growth of LAB at 32 °C with a bacterial inoculum of approximately 108 CFU/mL was predicted and subsequently compared with experimental results. The developed models demonstrated reliable predictive capability, with low-to-moderate Root Mean Squared Error (RMSE) across different substrates and growth parameters, ranging from 0.143 (vMaxAvg in apple) to 7.155 (LagAvg in orange). Following model validation, selected matrix–strain combinations were applied to develop food products, in which fermented by-products were incorporated as functional ingredients. The resulting formulations exhibited enhanced antioxidant activity and increased total phenolic content, as determined by DPPH (2,2-diphenyl-1-picrylhydrazyl) assay and phenolic analysis, reaching 56.56 mg GAE/100 g (p < 0.05) and 33.76 mg Trolox eq./100 g (p < 0.05), respectively.