Blood oxygen level dependent (BOLD) MRI data of kidney, while indicative of tissue oxygenation level (pO₂), is in fact influenced by multiple confounding factors, such as R₂, perfusion, oxygen permeability, and hematocrit. We aim to explore the feasibility of extracting tissue pO₂ from renal BOLD data. A method of two steps was proposed: first, a Monte Carlo simulation to estimate blood oxygen saturation (SHb) from BOLD signals and second, an oxygen transit model to convert SHb to tissue pO₂. The proposed method was calibrated and validated with 20 pigs (12 before and after furosemide injection) in which BOLD-derived tissue pO₂ was compared to microprobe-measured values. The method was then applied to 9 healthy human subjects (age 25.7±3.0 yrs) in whom BOLD was performed before and after furosemide. For the 12 pigs before furosemide injection, the proposed model estimated renal tissue pO₂ with errors of 2.3±5.2 mmHg (5.8%±13.4%) in cortex and -0.1±4.5 mmHg (1.7%±18.1%) in medulla, compared with microprobe measurements. After injection of furosemide, the estimation errors were 6.9±3.9 mmHg (14.2%±8.4%) for cortex and 2.6±4.0 mmHg (7.7%±11.5%) for medulla. In the human subjects, BOLD-derived medullary pO₂ increased from 16.0±4.9 mmHg (SHb 31%±11%) at baseline to 26.2±3.1 mmHg (SHb 53%±6%) at 5 min after furosemide injection, while cortical pO₂ did not change significantly at ~58 mmHg (SHb 92%±1%). Our proposed method, validated with a porcine model, appears promising for estimating tissue pO₂ from renal BOLD MRI data in human subjects.