Purpose: Dual energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI) permits quantification of visceral adipose tissue (VAT). However, DXA has not been validated against MRI in persons with chronic spinal cord injury (SCI). A predictive equation was generated from the measurement of VAT by MRI, a “gold” standard to quantitate VAT, compared to that of DXA, a method with several practical advantages. Method: DXA and MRI scans were performed in 27 participants with SCI. MRI multiaxial images were captured for VAT analysis. DXA-VAT was quantified at the android region (DXA-VATANDROID-VOL) using enCore software. Android regions of DXA and MRI were matched using android height. Volumes of multiaxial MRI-VAT and subcutaneous adipose tissue (SAT) were quantified for the android region (MRI-VATANDROID-VOL, MRI-SATANDROID-VOL) and total trunk (MRI-VATANDROID-VOL). Linear regression analysis was used to establish the proposed predication equations. The prediction equations were then applied to an independent sample that consisted of 98 participants with SCI. Bland-Altman analysis was used to determine the limits of agreement. Results: DXA-VATANDROID-VOL predicted 92% of the variance in MRI-VATANDROID-VOL (SEE = 252.5, p < 0.0005) and 85% of the variance in MRI-VATTRUNK-VOL (SEE = 1526.9, p < 0.0005). DXA-SATANDROID-VOL predicted 81.5% of the variance in MRI-SATANDROID-VOL (SEE = 458.2, p < 0.0005). Bland-Altman analysis revealed a high level of agreement between MRI-VATANDROID-VOL and DXA-VATANDROID-VOL (mean bias = 58.45 cm3). A predicted mean DXA-VATANDROID-VOL of 995.2 cm3 was estimated as the population-specific cut-off point for high levels of VAT. Conclusion: DXA-VATANDROID-VOL may accurately predict MRI-VATANDROID-VOL in persons with SCI. The ability of DXA to detect VAT changes in longitudinal studies in persons with SCI should be performed.