• Material and joint tests performed on 6082-T6 aluminium after thermal exposure. • Three lap joint configurations tested, showing distinct failure modes. • Stress–strain and fracture behaviour characterised via coupon testing. • Numerical models developed, validated, and used for parametric analysis. • Accuracy of design standards assessed and a modified bearing factor proposed. Structural aluminium alloys are commonly heat-treated to enhance their strength for load-bearing applications, but exposure to fire can degrade or completely eliminate these benefits. Even if a component withstands the fire, it may no longer meet design load requirements, making post-fire performance assessment essential. This study presents 16 material coupons tests and 12 experimental tests on 6082-T6 aluminium lap joints exposed to elevated temperatures (200°C, 300°C, and 400°C) prior to testing. Three joint configurations with varying bolt spacing were investigated, resulting in different failure modes: net section fracture, end bearing, and mixed failure. One unheated specimen per configuration served as a benchmark sample. Additionally, tensile tests on flat and flat grooved coupons were conducted to characterise the stress-strain and fracture behaviour after thermal exposure. The findings of the lap joint tests include load-displacement behaviour, as well as evaluations of failure loads and failure modes, and are reported in detail. Subsequently, numerical models were developed and validated against the experimental results. A parametric study was also carried out to investigate the influence of the bolt hole end and edge distance on the joint performance. The experimental and numerical results were used to evaluate the accuracy of existing design standards for predicting the resistance of aluminium alloy connections, including AS/NZS 1664.1, EN 1999-1-1 (Eurocode 9), and the provisions available in the literature. Based on the experimental and numerical data, a modified design equation for the bearing resistance factor is proposed to improve the prediction accuracy, and enable post-fire design that accounts for temperature-induced degradation.