Termite mounds are major sites of functional heterogeneity in the tropical ecosystems globally; through their prodigious influence on vegetation and soil perturbation. They aid soil aeration, water infiltration and catabolism of vegetative matter into nutrient rich humus. There is no documentation of a model for prediction of vegetation lifeforms with respect to mound basal radii, heights and altitude. Objective of this study was therefore to develop a model for rapid prediction of vegetation lifeforms (trees, shrubs, lianas and grass) abundance based on physiography (basal radii and heights) and altitude of the termite mounds. Study population of the mounds was unknown. Cross sectional research design was used. Saturated sampling was done where sixty accessible termite mounds were studied. Both basal radii and heights of termite mounds were measured using 50 m tape measure or hand-held inclinometer. Altitude data were captured by hand-held Global Positioning System (GPS). Trees, shrubs and lianas were identified visually and counted on the mounds while grass abundance was estimated using 0.3 m by 0.3 m quadrat on every termitarium. Multiple Linear Regressions were done to model vegetation lifeforms abundance based on termite mound basal radius, height and altitude. Results indicated that predicted MLR significantly (p ≤ 0.05) predicted trees, shrubs and lianas but not grass abundance. Predicted trees abundance = −89.2587 + 10.46157 (radius (m)) − 4.96989 (height (m)) + 0.074074 (altitude (m)), predicted shrubs abundance = 19.26065 + 6.780626 (radius (m)) - 6.09157 (height (m)) − 0.00822 (altitude (m)) and predicted lianas abundance = −24.9345 + 5.881659 (radius (m)) − 0.68423 (height (m)) + 0.020729 (altitude (m)). This study demonstrated significant effect of termite mound physiography on vegetation lifeforms abundance as well as developed a model for rapid prediction of their abundance on termite mounds.