The aim of the study was to develop an objective method to assess the vascular flow to the early corpus luteum (CL) in buffaloes using colour Doppler ultrasound data. Our hypothesis was that 3-dimensional (3D) volumetric analysis of vascularity would demonstrate lower variability between animals compared with conventional 2-dimensional (2D) analysis of single images. Wave emergence and ovulation was synchronized in buffalo (n = 16) using prostaglandin-GnRH based protocols. Colour Doppler ultrasonography (MyLab5, 7.5-MHz linear array, colour gain 65%) was performed daily from Day −2 to 4 (Day 0 = ovulation). Video clips of the ovaries (20 s at 18–28 frames per second, AVI) were recorded by slow and uniform free-hand movement of the transducer. Day 4 CL was used for analysis of vascular area and volume. For 2D vascularity assessment, 3 images (800 × 652 pixels, RGB, BMP) of each CL (at maximum apparent vascularity) were acquired through the clip image function on the ultrasound machine and analysed by ImageJ (Fiji) software (NIH, Bethesda, MD, USA). For 3D vascularity assessment, a portion of the video clip encompassing an entire ovary was identified and exported as a series of 2D TIFF images using Videomach software. The ultrasound scale bar was used to calculate the number of pixels per millimetre and to calibrate the X (horizontal) and Y (vertical) dimensions. For 2D analyses, the CL boundary was drawn using the free-hand manual selection tool in Fiji, the area of the CL (mm²) was recorded, and the border was then enlarged by 1.5 mm to include the peripheral vascular region of the CL. The colour threshold was adjusted to select the vascular region. The 2D vascularity score was calculated as the ratio of the coloured area to the enlarged luteal area. For 3D volumetric analyses, each series of TIFF images was imported as an image sequence in Fiji and colour thresholding (similar to 2D analysis) was applied to save a second TIFF series containing luteal vascular regions (coloured areas) only. The remaining volumetric analyses were completed in Imaris software using the ovarian volume (original TIFF series) and luteal vascular volume (second TIFF series) as separate channels. The Z-dimension thickness of each image was estimated by using the dimensions of a follicle within the same ovary (Z-axis diameter = mean diameter along X- and Y-axes). Similar to 2D analyses, the volume of the CL was obtained by drawing a border along the edge of the CL, the CL border was enlarged by 1.5 mm, and a 3D vascularity score was obtained by building a surface on the luteal vascular image and calculating the vascular to luteal volume ratio. The 2D vascularity score differed from 3D vascularity score (0.21 ± 0.02 v. 0.13 ± 0.02, paired t-test P < 0.01); however, variance did not differ (Bartlett’s test P = 0.32). Our initial results support the notion that the described technique of quantifying vascular volume of the corpus luteum may decrease the technical variability during image assessment and therefore better reflect the true vascularity compared with 2D image analyses.