<p>Cultivation-based land suitability has gained much attention to achieve sustainability in agroforestry in the face of a changing climate, increasing rate of population growth, and shrinking arable lands with continued urbanization. The olive tree or shrub is an evergreen tree and has been of immense importance as the principal source of edible oil, providing high nutritional value, providing health benefits, and an important source of income entirely in several regions. However, little attention was paid to sustainable olive farming and the identification of suitable plantation sites. Due to the economic, social and environmental importance of olive production in Pakistan, this paper aims to consider these points and identify suitable areas for Olive plantations across Pakistan using MCDA and AHP methods in ArcGIS Software. Utilizing GIS-based multi-criteria decision analysis (MCDA) techniques, with ancillary key factors such as elevation, precipitation, temperature, soil type, slope, land use, aspect, soil pH, soil drainage, and salinity, we determined the spatial site suitable for olive plantation, and validated accuracy by field observations. In addition, we used the analytic hierarchy process (AHP) to assign proper weights for the different criteria. Results show that 37% (35.80&#xa0;million ha) of the total area is highly potential for sustainable Olive followed by 35% (33.86&#xa0;million ha) that fall under moderate suitability cultivation across the country, 28% (27.09&#xa0;million ha) showed poor cultivation sites. Suitable sites show limited overlap with existing agricultural land-use systems, suggesting that their development is unlikely to adversely affect food security programs, particularly since olive is itself an agricultural crop commonly integrated into farming systems. This study outcome emphasizes investment in olive tree expansion in proposed suitable sites to get the maximum economic benefits. Indeed, this information will be very useful in assisting stakeholders and decision-makers with suitable olive tree plantations, both for agriculture and forest managers, and operational planning which may increase Pakistan’s olive production. It was discovered that MCDA was a useful technique for decomposing the problems associated with determining and categorizing potential afforestation sites in forest management.</p> Graphical Abstract <p></p> <p>This visual summary serves as a pivotal entry point into the research, offering a concise overview of the study’s core findings and methodologies. The graphical abstract above shows the workflow of identifying areas suitable for growing olive crops in Pakistan based on GIS MCDA using the AHP model. In the graphic, there are five main elements including: Data – the representation of the study area as well as important environmental and soil layers (elevation, slope, rainfall, temperature, land use, soil type, pH, drainage, salinity, and aspect); Analyses – showing how to proceed from resampling and normalization to overlay and suitability mapping; Model – the weightage scheme of the AHP model used to determine the weightage of the factors; Result – the result of land suitability in which 37% of the country is highly suitable, 35% moderately suitable, and 28% unsuitable; and finally the Conclusion– showing that no suitable sites exist on current agricultural lands, allowing for further expansion. The logical sequence of the graphical abstract allows understanding the process from the collection of data to modeling and important results. Use of high-quality graphics, well-matched color schemes, and proper labeling helps to make it understandable and fast to perceive the complex information about the spatial aspect. All things considered, the described graphical abstract is a concise way to introduce the work in a graphic format, which will help to understand the aim and results of the paper just by looking at it.</p>