Faster eating rates have previously been associated with higher ad libitum energy intakes, and several studies have manipulated eating rates and intake by changing food textures. Food texture based changes to slow eating rates can produce reductions in energy intake without affecting post-meal satisfaction or re-bound hunger. However, an understanding of how specific food textures and instrumental texture properties influence oral processing behaviour remains limited. The current study sought to establish relationships between objective measures of oral processing behaviour (i.e. number of bites, average bite size, total chews, chews per bite, oro-sensory exposure time and eating rate) and instrumental measures of a food texture including hardness, adhesiveness, springiness, cohesiveness, chewiness, resilience and modulus. Across two studies, behavioural coding analysis was completed on video-recordings of participants consuming fixed portions of a wide range of different solid foods (n = 59) to derive objective measures of oral processing behaviours. These measures were correlated with instrumental Textural Profile Analysis (TPA) for the same set of foods. Significant correlations (p < 0.05) were found between oral processing parameters and texture properties (i.e. springiness, cohesiveness, chewiness and resilience). No significant correlations were found between hardness and modulus and oral processing parameters. Protein content of the food was associated with springiness and chewiness, which may help to further reduce eating rates. In terms of the ‘breakdown path model', hardness and modulus might represent degree of initial food structure while springiness, cohesiveness, chewiness and resilience seem to determine how fast the degree of structure is reduced to the swallowing plane. Water content and adhesiveness were associated with level of lubrication that is required before reaching the swallowing plane. The current study highlights opportunities to understand eating rate (g min−1) through the breakdown path model and the potential for specific features of a foods texture to influence rate and extent of energy intake. The correlation between instrumental texture properties and oral processing patterns provides guidance on the parameters that are likely to produce ‘faster' and ‘slower' versions of foods, and suggests how texture modifications could be applied to moderate eating rate and energy intake within meals.