Background Bone marrow lesions (BMLs) are a known risk factor for incident knee osteoarthritis (OA), and deep learning (DL) methods can assist in automated segmentation and risk prediction. Purpose To develop and validate a DL model for quantifying tibiofemoral BML volume on MRI scans in knees without radiographic OA and to assess the association between longitudinal BML changes and incident knee OA. Materials and Methods This retrospective study included knee MRI scans from the Osteoarthritis Initiative prospective cohort (February 2004-October 2015). The DL model, developed between August and October 2023, segmented the tibiofemoral joint into 10 subregions and measured BML volume in each subregion. Baseline and 4-year follow-up MRI scans were analyzed. Knees without OA at baseline were categorized into three groups based on 4-year BML volume changes: BML-free, BML regression, and BML progression. The risk of developing radiographic and symptomatic OA over 9 years was compared among these groups. Results Included were 3869 non-OA knees in 2430 participants (mean age, 59.5 years ± 9.0 [SD]; female-to-male ratio, 1.3:1). At 4-year follow-up, 2216 knees remained BML-free, 1106 showed an increase in BML volume, and 547 showed a decrease in BML volume. BML progression was associated with a higher risk of developing radiographic knee OA compared with remaining BML-free (hazard ratio [HR] = 3.0;